Product Description
Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop!

Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You’ll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to:

• Analyze all types of sequences
• Use all types of databases
• Work with DNA and protein sequences
• Conduct similarity searches
• Build a multiple sequence alignment
• Edit and publish alignments
• Visualize protein 3-D structures
• Construct phylogenetic trees

This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what’s going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you’ll be searching databases and analyzing sequences like a pro! ... Read more

Customer Reviews (18)

A great start!
Very simple and very well explained, I recommend this book to all who show interest in using bioinformatics as a research tool.

great reference
As a Phd student in biology, this book offers great reference for bioinformatics in a clear and smooth manner. it explains briefly the concept behind few notions and then shows you how to search, interpret the data you receive. no previous knowledge of bioinformatics is necessary to have this book. the only problem is that several websites either change/close their website or change the application format and it becomes hard to follow the book instructions. however it is a very important tool for researchers.

Good Purchase
Good concepts for a beginner ad intermediate level. Concepts are clearly explained and are easy to understand.

Overall a Good Book on Bioinformatics
This is overall a good book on bioinformatics. If you like the Dummy series, you will like this book. It's more thorough on the biology side of bioinformatics than on the "information" side. However, the concepts are explained in an easy to understand fashion. Worth the price.

Thorough, in-depth introduction. The "for dummies" is misleading
Many people are derisive about the "for Dummies" series, believing them to be too simplistic and sometimes even an insult to their intelligence. That can hardly apply to this book, as there is nothing "dummy" about it. You need a significant background in biology and chemistry in order to understand most of it. You need to understand the amino acid structure of proteins, the structure of DNA and many fundamental principles of data analysis. Some knowledge of the structure and operations of databases is also needed. The authors include a large number of web sites containing additional information and that can run analyses.
The coverage is so thorough and detailed that this is the only "for dummies" book that I have seen that could honestly be recommended as a college text.And not just at the freshman level either.
... Read more

Product Description
With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you're a biologist with little or no programming experience, starting out in Perl can be a challenge. Beginning Perl for Bioinformatics is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises. By the end of the book you'll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming.Amazon.com Review
Biology, it seems, is a good showcase for the talents of Perl. Newcomers to Perl who understand biological information will find James Tisdall's Beginning Perl for Bioinformatics to be an excellent compendium of examples. Teachers of Perl will likewise find the text to be filled with fresh programming illustrations of growing scientific importance. Seasoned Perlmongers who want to learn biology, however, should search elsewhere, as Tisdall's emphasis is on Perl's logic rather than Mother Nature's.

Departing from O'Reilly's earlier monograph Developing Bioinformatic Computer Skills, Tisdall's text is organized aggressively along didactic lines. Nearly all of the 13 chapters begin with twin bullet lists of Perl programming tools and the bioinformatic methods that require them. Likewise, the chapters end with exercises. String concatenation is illustrated with gene splicing, and regular expressions are taught with gene transcription and motif searching.

Tisdall emphasizes sequence examples throughout, leading up to an introduction to a Perl interface for the NIH GenBank biological database and the widely used BLAST sequence alignment tool. After a brief discussion of three-dimensional protein structure, he returns to sequence extraction and secondary structure prediction.

Tisdall's goal is to boost the beginning programmer into a domain of self-learning. He imparts essential etiquette for the success of programming newbies: use the wealth or resources available, from user documentation to Web site surveys to FAQs to How-To's to news groups and finally to direct personal appeals for help from a senior colleague. A well-plugged-in bioinformatics Perl student will soondiscover Bioperl, an open-source effort to bring research-grade bioinformatic tools to the Perl community. Bioperl is described briefly at the end of Tisdall's book and will reportedly be a forthcoming title of its own in the O'Reilly bioinformatics series.

Although he introduces bioinformatics as an academic discipline, Tisdall treats it as a trade throughout his book. He indicates that open questions and computational hard problems exist, but does not describe what they are or how they are being tackled. Ultimately, Tisdall presents bioinformatics as another arrow in a bench scientist'squiver, very much like HPLC, 2D-PAGE, and the various spectroscopies.

As odd as a "bioinformatics-as-tool" book may be to its research proponents, the reduction of bioinformatics to trade status both deflates and vindicates the years of research, as Tisdall's work attests. --Peter Leopold ... Read more

Customer Reviews (30)

Not really for beginners!
It seems to be a very good book, but not basic at all! You need to know a lot of perl language before using this book.

I loved this book:
If you haven't programmed in perl before, this book is perfect for learning.It also teaches very low level bioinformatics skills that'd probably help an undergraduate get their next internship.I was clueless to perl, and programming for that matter, when I got this book a long time ago.I painfully flipped each page from front to back, because it 'is' a technical book, and absorbed everything as much as possible.This book set me off in a direction that I never imagined.Although we're on the brink of version six of the language, this book will do you right in any aspect of computer programming.For a 'beginner' looking to get into any language, this book is for you.It's painful, but try and take the time to really learn the information the book presents.It not only teaches you perl, but gives you a peek into the numerous databases and resources that exist as well as a terrific job of teaching you how to use regular expressions.

In the end, you'll have the foundation to become whatever kind of perl programmer you desire.If you're looking into bioinformatics, or a bioinformatician looking to learn, I recommend this book as well as 'Programming Perl', 'Mastering Perl for Bioinformatics', and 'BLAST'.'BLAST' is fairly easy to breeze through and does a good job of explaining everything you would need to know.'Mastering Perl...' picks up where this book left off, and 'Programming Perl' is one of the best buys I ever made, in regards to perl.I know these are all O REILLY books, but they're probably the best source for perl books out there.I'm not pitching their books either.Lastly, if you have the time I recommend you crunch on through 'CGI Programming with Perl'.Although the book is a bit out of date, it's definitely another 'piece' of the puzzle for someone to become a LAMP programmer.

good book for biologists
Very good book in perl for those biologist trying to merge their career into bioinformatics.

Beginning Perl is an excellent book.
Beginning Perl for Bioinformatics is an excellent, well-written text for the non-specialist person who wishes to program in perl.Although perl is indeed very powerful some concepts are rather unique and difficult to grasp if one understands other scripting languages.For a beginner, the book provides the necessary detail as required so as to progress rapidly.I would recommend it highly.

Great for Biologist that Don't Know How to Program
If you know anything about how to program then this book is NOT for you.This book is more geared towards biologists that know nothing about programming.If you fall in this category I recommend this book for you.Seriously, buy it and learn how to program so you can stop bugging people with better things to do to parse your BLAST output and FASTA files for you.In this day and age there is no reason why a biologist shouldn't have basic scripting abilities. ... Read more

Product Description
The bestselling introduction to bioinformatics and functional genomics—now in an updated edition

Widely received in its previous edition, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded Second Edition, it continues to be the go-to source for students and professionals involved in biomedical research.

This edition provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include:

• Several fundamentally important proteins, such as globins, histones, insulin, and albumins, are included to better show how to apply bioinformatics tools to basic biological questions.
• A completely updated companion web site, which will be updated as new information becomes available - visit www.wiley.com/go/pevsnerbioinformatics
• Descriptions of genome sequencing projects spanning the tree of life.
• A stronger focus on how bioinformatics tools are used to understand human disease.

The book is complemented by lavish illustrations and more than 500 figures and tables—fifty of which are entirely new to this edition. Each chapter includes a Problem Set, Pitfalls, Boxes explaining key techniques and mathematics/statistics principles, Summary, Recommended Reading, and a list of freely available software. Readers may visit a related Web page for supplemental information at www.wiley.com/go/pevsnerbioinformatics.

Bioinformatics and Functional Genomics, Second Edition serves as an excellent single-source textbook for advanced undergraduate and beginning graduate-level courses in the biological sciences and computer sciences. It is also an indispensable resource for biologists in a broad variety of disciplines who use the tools of bioinformatics and genomics to study particular research problems; bioinformaticists and computer scientists who develop computer algorithms and databases; and medical researchers and clinicians who want to understand the genomic basis of viral, bacterial, parasitic, or other diseases.

Praise for the first edition:

"...ideal both for biologists who want to master the application of bioinformatics to real-world problems and for computer scientists who need to understand the biological questions that motivate algorithms." Quarterly Review of Biology

"… an excellent textbook for graduate students and upper level undergraduate students." Annals of Biomedical Engineering

"…highly recommended for academic and medical libraries, and for researchers as an introduction and reference…" E-Streams ... Read more

Customer Reviews (7)

Excellent Text
This is the third Bioinformatics text that I have read in the past three years. And, this particular text is light year *ahead* of the others. It is dense, but it gives the background and big-picture that many of the others are lacking.

The text does not always flow - as if different sentences from different sources were thrown together without transition. As the text does cite many papers, this is acceptable. However, a review and small edits to help with the flow would make the book better.

Regardless, it's the best text on this subject that I am currently aware of.

Excellent Learning Text, Well Written
I spent a lot of time looking for a bioinformatics text book that focuses on sequence analysis for a course I'm teaching.I decided that Mount's book was too wordy and unclear, and while I liked Orengo's book quite a bit, it required a good amount of knowledge up-front to follow it.Pevsner's book is laid out in a logical fashion and is designed to teach the molecular biology types the underlying principles of bioinformatics.It discusses pairwise alignments, substitution matrices, multiple sequence alignments, profiles, position-specific scoring matrices and phylogenetic trees with a good amount of detail.There's also a chapter on microarray analysis, but to get into that deeply I recommend Draghici's book.
The 2nd half of the book discusses the genome organization and evolution of a variety of organisms (viruses, bacteria, eukaryotes, human), and was great for bringing me up to date on these topics.
I strongly recommend this as a textbook for undergraduate or graduate students learning bioinformatics.

Purchased for Class
I purchased this item new for a class I am in.I have only read a small amount as of yet, but it seems to be a well written text.The book came very quickly after my purchase.

Excellent Condition
The book as recieved from seller in exellent condition. Fundamental concepts of Bioinformatics are well explained.

Highly Recommended
"...an intriguing work targeted toward biologists wanting to solve problems...provides a compendium of many biological insights and breakthroughs and will be a useful resource...highly recommended." (Choice, Vol. 41, No. 7, March 2004) ... Read more

Product Description
An Introduction to Bioinformatics introduces students to the immense power of bioinformatics as a set of scientific tools. The book explains how to access the data archives of genomes and proteins, and the kinds of questions these data and tools can answer, such as how to make inferences from data archives and how to make connections among them to derive useful and interesting predictions.

Blending factual content with many opportunities for active learning, An Introduction to Bioinformatics offers a truly reader-friendly way to get to grips with this subject, making it the ideal resource for anyone new to the field.

Features
- Strikes a careful balance between biology and computer science, introducing those aspects of computer science which underpin the subject without demanding detailed prior knowledge.
- Contains numerous learning features, including exercises, problems, and WebLems.
- Retains the eloquent style and clarity of explanation for which the author is renowned.
- An Online Resource Centre includes figures from the book available to download to facilitate lecture preparation, as well as a variety of interactive resources, including web links, 3D structures, and data sets.
ew to this Edition
- New chapter on biological organization in space and reflects recent advances in genomics, transcriptomics, proteomics, and metabolomics.
- New chapter on scientific publications and archives provides a state of the art inventory on sourcing scientific literature.
- Expanded coverage of structural bioinformatics.
- Enhanced Online Resource Centre, with new guided tours of key websites, and lab assignments to support the in-depth exploration of concepts and themes covered in the book. ... Read more

Product Description
This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems.

The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively.

An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.

PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Authors' website. ... Read more

Customer Reviews (9)

Great text
This text is a must-have for any student or scientist that is serious about learning the fundamentals of bioinformatics.

Good choice for an absolute beginner
I find this book well-written and friendly to people who have not been exposed to algorithmic ideas. Biologists who are keen to understand algorithms that underpin all bioinformatics softwares will get a good dose of confidence after reading this book. To get the best out of this book a reader should test the algorithms explained in the book using a familiar programming language. Experienced people looking to "level-up" their expertise are likely to be disappointed - this is definitely a book for beginner / intermediate level folks.

Uma excelente introdução à bioinformática
Este livro é excelente por várias razões. Entre elas posso citar o fato de estar totalmente voltado ao aprendizado por exemplos, sempre de forma a relacionar um problema computacional com um problema em bioinformática. É um livro muito abrangente, cobre muito bem os tópicos relacionadosa alinhamentos e comparações de sequências. Seu capítulo sobre Algoritmos com Grafos é o meu preferido. O autor consegue passar as noções fundamentais com muita simplicidade, de forma que qualquer pessoa possa aprender num ritmo bem rápido.

Excellent algorithms exercise & bioinformatics intro
This is the first book that I've read regarding bioinformatics, so Im updating this as my class moves along. You better have a grasp of basic data structures prior to beginning this book and background with a programming language as there is very little hand-holding in this text. A bio background makes it all more interesting but certainly is not critical. There are no sample code or sources printed with the book nor is there an included CD nor answers to exercises. There is an associated web site where some ideas may be had and errata found/reported, but its not very active that I have seen. The pseudo code in the book is very python-like so easy to make use of. I personally transfer the book's concepts to C/C++ (habit) without much problem, except sometimes my results differ from the book. Apparently these are book bugs, so be sure to check the web site out if unexpected things pop up.
Presently my class is in chapter 8 (of 12) and looking back I would like to caution that some data processing algorithms will drive a computer's CPU quite hard so be aware of battery-munching & heat. My only bones with this book so far are the alphabet soup of variables and lack of answers to exercises. It would be nice if variable definitions were refreshed at the beginning of pseudo code samples.
I like this book as an algorithms text over traditional texts because the applications are much more fascinating. Imagine searching for something and you don't know where that something is. On top of that add not even knowing exactly what it is you are looking for. And when you do find it, its not even in the data searched! This may sound unlikely or even impossible, but it is neither. Rather, its very cool.
4-stars

Should really be called Intro Data Structures and Algorithms
I knew most of the stuff before I opened the first page.It's basically teaching data structures 101 using a few watered down bioinformatic problems for motivation.The lack of applied problems involving real data was most disappointing.It does have a lot of the type questions that some nerd (me one day :P) might ask you on a job interview.The questions are also a good way to kill time if you have nothing better to do.I give the book credit for stressing dynamic programming.I believe that this is one of the most important concepts in problem solving.

3 stars because I think it is a fairly good introduction for fledgling computer scientists BUT not a good reference for comptuer scientists trying to apply their skills to solve bioinformatic problems.

... Read more

Product Description
Modern bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. Building Bioinformatics Solutions provides a comprehensive introduction to this methodology, explaining how to acquire and use the most popular development tools, how to apply them to build processing pipelines, and how to make the results available through visualizations and web-based services for deployment either locally or via the Internet. The main development tools covered in this book are the MySQL database management system, the Perl programming language, and the R language for statistical computing. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS.

This advanced textbook is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed. Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills. ... Read more

Customer Reviews (2)

Great Book! Responsible Authors!
This is a great book,I am very satisfied with it.

In fact, this book combines the most popular tools in bioinformatics:Perl, R and MySQL.

Some of us may be expert for one or two of these tools. But how to systemically to use them together, this book gives answers.

It aslo gives direction of how to go further if you want to master one of these tools.

Plus,it has a lot of practical examples which you can easily transform for your own work.

And I must say the authors are very responsibe. They answered my questions promptly and in details. I really apprecitate this.

Thank you.

Excellent book!
I'm very satisfied with this book.
Very clear explanations and examples.
Contains all the relevant chapters that one needs to get into bioinformatics.
... Read more

Product Description
Bioinformatics is a growing field that attracts researchers from many different backgrounds who are unfamiliar with the algorithms commonly used in the field. Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the development of simple programming exercises . Ideal for those with some knowledge of computer programming languages, this book emphasizes Python syntax and methodologies. The text is divided into three complete sections; the first provides an explanation of general Python programming, the second includes a detailed discussion of the Python tools typically used in bioinformatics including clustering, associative memories, and mathematical analysis techniques, and the third section demonstrates how these tools are implemented through numerous applications. ... Read more

Customer Reviews (2)

A very well done book on implementing algorithms in Python
The author is a well-liked professor at George Mason University, and he has been teaching bioinformatics programming from beginning to advanced for several years. This book is formed somewhat like his lectures for those classes. He assumes you have a background in bioinformatics and that you already know some Python. From there he goes on to show you many of the problems you may be faced with in bioinformatics coded in Python. He actually says that he is trying to answer the question most commonly asked by his students - "How do I put what you just taught into code?".

If you need to a good book on bioinformatics algorithms that is language agnostic may I suggest An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) as well as Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. The latter book is especially good for computer science students seeking bioinformatics knowledge. Let me also point out that this book is of use for people seeking Python solutions to non-bioinformatics problems. Since much of bioinformatics has to do with dealing with strings, trees, and statistical analysis of data, students of subjects other than biology can find uses for this book.

Do note that the book's one great problem is that it is using Python 2 not Python 3. It is the fault of the designers of Python that most everything written for Python 2 becomes broken in a Python 3 interpreter rather than the fault of this author, yet the problem remains. Fortunately, Python looks enough like pseudocode that you can probably do any translations necessary without too much hair-pulling.

Good book, but learn python first.
Python isn't as popular as some other languages amongst bioinformaticans , but it is probably gaining acceptance and this book is a result of it. The author is a practising bioinformatician. This is a good book. It discusses all the mathematical concepts that bioinformaticians usually use, and how they can be implemented in python. It requires, as the author himself says, a fairly good knowledge of mathematics and basic molecular biology. In my opinion, it also requires a good familiarity with the python language. There is a very small introduction to it in the first chapter but beginners will need more exposure to the language than that. Since I can code in python, and I needed a book that jumped straight into the bioinformatics part, I like it. ... Read more

Product Description
As more species genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories. Related Titles from the Publisher Discovering Genomics, Proteomics, and Bioinformatics Emerging Model Organisms Genomes Proteins and Proteomics: A Laboratory Manual A Short Guide to the Human Genome ... Read more

Customer Reviews (20)

One of the worst text-books I have ever read
I used this book in an introduction level class to bioinformatics and it was worse then useless. The book is much more a survey of literature then anything else and so if you are not already very familiar with the topics the book does not provide enough details for you to get very far at all. Although to be fair most of the books on bioinformatics out at the time and the two years after were not much better, but I felt this was near the bottom of the pile. "Fundamental Concepts of Bioinformatics", ISBN: 0-8053-4633-3 when it came out was miles better, although even that book had tons of warts. If you are looking for a reference then this book is okay, but by the time I am writing this review you assuredly can find a more modern book.

Part of the problem with books on bioinformatics is that, every book makes very different assumptions on your base level of knowledge of the various critical subjects needed: biology, chemistry, computer science and math. Most strike a pretty poor balance on the assumptions made and vary from way too basic to useless to anyone who is not already familiar with the field. My suggestion is to check out any book you are considering because how good the book is will vary greatly on your background.

more challenging than trying to unravel the human genome.
I used this book to teach a bioinformatics course in a foreign language because it was only one of two available in both english and chinese.I'm not sure it wouldn't have been less confusing to simply use a english textbook and let the students translate the text for themselves.To give the author credit, he has compiled an enormous quantity of information and made it available in a single location and that is no mean feat.At the very least, it is a valuable starting point to find both useful references to better explanations and software appropriate to almost any analysis you might want to do.On the downside, the prose is a tangled mess and is beyond comprehension in places.there are points where, even though i understand the underlying theories used throughout the book, i still couldn't figure out some of the examples used to illustrate particular methods.For example, there are some figures which have captions which run for a page and a half.Finally, in the majority of cases, the figures are taken directly from key papers on each topic, and associated explanations consist of sentences copied verbatim from the text. I may be doing the author a gross injustice here, but in many of the explanations, i was left with the same impression i get when reading students papers when they have copied something out of a textbook, without really understanding what is going on.Having said all of the above, i would still recommend taking a look at this book, but be ready to access the excellent list of references if you want a more insightful understanding of many of the methods described throughout.

Leaves something to be desired
I took Dr. Mount's class at the U. or Arizona, and he's a really smart guy, but the man can't explain anything. It's not just his book either; his lectures are just as cryptic. I went to class thinking I understood the concepts, but then I got totally confused when he lectured. I would try to clarify things with the book, and again, I'd get even more confused. Someone who reviewed this book earlier said that he tends to use 10 words where he should use 1; I couldn't agree more. The figures in this book also need a major overhaul, and he should definitely include more examples of the many complex concepts he talks about. While I have no doubt that there is plenty of useful information in there, getting anything out of it is a chore. I would only recommend this book to someone who already had a strong knowledge of bioinformatics concepts.

Bioinformatics: Sequence and Genome Analysis by David W. Mount [Paperback]
Book is a good reference textbook for Bioinformatics.Of course the material covered is technical and dense, but that is unavoidable for the subject matter that the book covers.

A good book despite criticism
I don't understand such a lot of bad comments about this book. In this book concepts are presented in an intelligent way, because the book is as quantitative as the biologist's requirements are. Everithing is sufficient to comprehend which are the things' mathematical basis but avoiding time-comsuming and ready-to-forget extra info. Other books are only for matematicians because they are sometimes full of numbers and complicated equations, while other ones are so simple that I imagine them usefull only for non-biologists (matematicians again above all).
This is a book that is usefull as an introduction for the initial graduate level bioinformatician (biologist) and as a short description of the techniques that we use to matematiciansaimed to collaborate.

Finally I am not in agreement with some coments about what is Bioinformatics. Most of them carried out by some non-biologists here. Bioinformatics is Biology. Of course we use mathematics, but as far as we USE them, bioinformatics is not mathematics. We do not develope Mathematics, but Biology state of the art. Bioinspired algorithms, in the other hand, are pure mathematical concepts, even if they are insipred in biology. Let Bioinformatics be what it is, a quantitative and statistical part of pure Biology.

This is a good book if you are not an expert in Bioinformatics but you have in mind to be one. Study this book entirely as your first one and go directly to the difficult ones. For me, it is the shorter reading path to bioinformatics expertise nowadays. ... Read more

Product Description

Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies. 

The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively.  In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure – predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology.

The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and flow diagrams to give an overview of the conceptual links within each topic. 

Customer Reviews (2)

Fantastic not only for scientists, but also for computer programmers.
This review was originally published in SciTech Lawyer, an American Bar Association Publication, in February 2008.

Understanding Bioinformatics
written by Marketa Zvelebil and Jeremy O. Baum
published by Garland Science, 2008
ISBN 0-8153-4024-9 (10 digit) or 978-0-8153-4024-9 (13 digit)


When I volunteered to write a book review in the field of bioinformatics, I couldn't exactly shop at the local bookstore.Being both intimidated and in a big hurry, I scanned Amazon's choices and I chose the one that sounded easiest:Understanding Bioinformatics, a recent paperback written by Marketa Zvelebil and Jeremy O. Baum.The title reminded me of Essentials of Molecular Biology by David Freifelder, the 1985 condensation with pretty pictures for budding biotech patent attorneys whose college papers were typed on an actual typewriter. However, shopping online and taking the easy route is risky; too many karmic variables.It turns out that the book weighs about four pounds; and even though it has plenty of pictures, it also has plenty of calculus.

Even so, for those of you who are fairly up-to-date on this subject, you will find this book comprehensive and current.It is loaded with information, and seems to cater to someone who would sit down at a computer with the book on the edge of her desk, picking through for pointers.Anyone who masters this text can, without cracking even a small smile, consider himself an expert on the subject.

Understanding Bioinformatics is, however, written for a variety of audiences, with each chapter formatted such that a reader can choose how technical to get.For right-brainers, the prose is easy to read and the graphics are great for memory retention.The book ramps up from fairly easy to extremely technical quickly but smoothly, with an increasing need for calculus as the book progresses. I will admit that the later chapters were slow-going.However, the authors are superb communicators and offered the information such that the concepts are attainable, even to someone who graduated in 1991, practiced biotech patent law for ten years, took a detour to make artisan cheese, and recently rejoined the lawyer game.In other words, no matter what your technical background, this book is written in a style that makes the basic topics simple, and the difficult topics relatively easy.Even though the authors mine the depths of bioinformatics, they never get distracted or off-course.This text is probably the only one you would need on the subject, with the next step being journal articles, conferences, or discussions with other bioinformatics enthusiasts.

For left brainers, there is plenty of math in this book.To be honest, I flashed the equations around my office and home, just to prove that my job is really, really hard. People were suitably impressed.I'm not sure that the authors had "fodder for patent lawyers to show off to immigration lawyers" as a goal when writing it, but I can vouch that it is a decent enough reason to buy the book.

The authors assume a college level understanding of molecular biology, evolutionary biology and genomics, but they are kind enough to give gentle reminders if you need a refresher.Happily, interesting pieces of trivia are sprinkled throughout, in separate, somewhat stylish boxes.The glossary is adequate.The index is five pages, but the subjects are printed in a tiny font, making it difficult to read.The small font size in an informatics book made me snicker, but just a bit.

My favorite part of this book is that the authors admit that you are a reader of the book, and that you have expectations and desires.For instance, at the beginning of each chapter, the authors promise that after you read the chapter, you should be able to do and know certain things.Upon reading Chapter 11, you should be able to "discuss the statistical scoring of patterns."With whom, I wonder.But, their unending confidence in my abilities encouraged me to give each new chapter a try.

Another fantastic feature is the "Mind Map," a diagram at the beginning of each chapter, with color-coded ideas that make literal line connections between concepts.I loved those Mind Maps!I also got a kick out of the "Flow Diagrams" that they throw in with the start of new concepts within the chapters.The Flow Diagrams tell you, for instance, "The key concept introduced in this section is that multiple sequence alignments can be produced by a variety of closely related techniques, which are based on the pairwise sequence alignment methods."In other words, if you don't understand the sentence in the Flow Diagram, make sure you read the section, or skip it, if you do.

If you have read this far, you are obviously genuinely interested in bioinformatics, so I will give you the details.

Part 1 is Background Basics.Chapters 1 and 2 cover molecular biology basics, and are nice to have in the book, but most biotech patent lawyers already know this stuff. Every now and then, the authors remind the reader that science is science, and that you should not assume that things are really as you have been taught.For instance, Box 1.2 header screams:"Things are usually not that simple!" and strongly warns the reader not to assume that everyone agrees what the definition of a gene is.Refreshing, really.Chapter 3 covers database basics, and I was able to understand it even though I do not consider myself a computer person.For those of you who are computer people, this is stuff that you would know off the top of your head, and would not bother reading.The authors acknowledge that the first three chapters are warm-ups, and not intended to be the way you learn this information if you are serious about it, and offer further reading suggestions.Plus, they throw in several appendices for good measure, on subjects such as: probability, information, and Bayesian analysis; molecular energy functions; and function optimization.

Part 2 is Sequence Alignments.Chapter 4 discusses producing and analyzing sequence alignments, and covers the basics, in a regimented, but conversational, manner.Biotech patent attorneys should definitely know this information, and the authors deliver it painlessly. Chapters 5 and 6 dig deeper into alignments, including how to do multiple sequence alignments, as well as presentation and critical analysis of the results.

Chapter 7 kicks off Part 3, on Evolutionary Processes, with phylogenetic tree reconstruction and some information on molecular evolution.Along with Chapter 8, which teaches specifically how to build phylogenetic trees, this section strikes me as most often applicable to scholarly endeavors.Even so, I enjoyed it immensely.One reason to read this chapter is to learn how each type of tree is flawed in its own way, so that you stop and consider what you are seeing, for instance, in an invention disclosure.

Part 4 is Genome Characteristics, with Chapter 9 covering gene prediction, promoter and splice site detection, and statistical analysis.Chapter 10 compares various computer programs for gene detection, and provides tips for predicting eukaryotic gene signals and exon/intron structure.The authors once again warn readers against relying too heavily on the technology and concepts of the day, and remind scientists to question their methods and delivery of results.This theme underscores the fluidity of bioinformatics, and, for patent attorneys, the need to know what you are talking about when writing a specification or arguing a motion.

Part 5 deals well with Secondary Structures, including, in Chapter 11, laying out the types of prediction methods, making sure the reader knows the tools available and ways to use them, and following up with statistical analysis and caveats.Prediction of transmembrane protein structure is also reviewed, including a selection of prediction programs for helices, and when to choose which program or technique.This chapter also provides coil and RNA secondary structure prediction tools and considerations.Chapter 12, Predicting Secondary Structure, has a lot of calculus and is very intimidating if you thought you would actually need to prove mathematically that, as Box 12.1 states,"Neural networks must be parameterized by training before use for prediction."If you stick to the text and the figures, however, most of the concepts and vocabulary are attainable to even the oldest and slowest among us.Moreover, if you ever need to know the math details, this is the text you need by your side.

Part 6, Tertiary Structure takes Part 5 to another dimension and complexity.I have to say that anyone who can teach this Part is Nobel Prize material.My brain chugged through it the way my Chevy Vega took to the Bloomington hills, slowly but surely.I mostly credit the authors for their patience and understanding in my conquering the material, but Starbucks certainly contributed.Chapter 13 digs deep into potential energy functions and force fields, obtaining a structure by threading, principles of homology modeling, steps in homology modeling, automated homology modeling, and then, to give you a break, provides a concrete example of the PI3 Kinase p110á.Chapter 14, Analyzing Structure-Function Relationships, an inherently interesting subject to me (no kidding), was no disappointment, although I was surprised and reluctantly happy to find information that I didn't know.There are more programs out there than I previously thought, and the authors describe each with precision and clarity.

Part 7, Cells and Organisms, covers Proteome and Gene Expression Analysis (Chapter 15) and Clustering Methods and Statistics (Chapter 16), and Systems Biology (Chapter 17) are chunky, but again, the concepts are there, and you can use the text on many different levels.If you are a computer programmer, you would do well to check out the problems encountered in spot detection on 2D gels, and how mass spectrometry analysis of a 2D gel increases reliability of the analysis.Over and over, I was impressed at the integration of the biology, math and graphic expression of data and results.The authors have a gift for communicating the importance of, and methods for, communication.This text provides a common vocabulary for biologists and computer programmers to speak to each other, even though they may be too shy to do it.

All in all, despite my initial horror when I realized that this review would take more than one unbillable hour, I am glad I did it.I was happy to find that I knew more than I thought I did, and the authors' confidence-building tone and presentation drove me through the things I didn't.Plus, it is oddly satisfying to criticize a woman and a man who are absolute, no-doubt-about-it geniuses.In sum:I recommend it - great book!And now that I have it on my shelf, I feel, and more importantly, look, smarter.

understanding bioinformatics
The book I ordered was old but the one I received appeared as brand new. And also it reached unexpectedly sooner during Christmas holidays!! ... Read more

Product Description
Bioinformatics--the application of computational and analytical methods tobiological problems--is a rapidly evolving scientific discipline. As a resultof advances in gene sequencing, biological databases are growing exponentially.It's impossible for even the most zealous researcher to stay on top ofnecessary information in the field without the aid of computer-based tools.Written in a clear, engaging style, Developing Bioinformatics ComputerSkills is for scientists and students who are learning computationalapproaches to biology, as well as for experienced biology researchers whoare just starting to use computers to handle their data. The book covers theUnix file system, building tools and databases for bioinformatics,computational approaches to biological problems, an introduction to Perl forbioinformatics,data mining, data visualization, and tips for tailoringexisting data analysis software to individual research needs. DevelopingBioinformatics Computer Skills will help biologists develop a structuredapproach to biological data as well as the tools they'll need to analyze it. ... Read more

Customer Reviews (29)

horrible
This book is the worst I've ever purchased. It has been no help whatsoever.It had a couple examples of PERL programming...big deal.

The 5-star ratings are obvious shills (one reviewer wrote a very long review and has never reviewed anything else)

Good introduction, somewhat uneven
This book is a good introduction to Bioinformatics and to what it takes to get started in the field. Some reviewers deride it as too superficial or as too Unix-centric, but I think those are two of its strengths. The authors lay no claim to having written the definitive work on the subject of Bioinformatics, and they freely admit that they come in with a certain bias. If you are serious about Bioinformatics this won't be your last book anyway, but it'll get you started.

That said, I found the material a bit uneven. The authors tend to jump from almost trivial stuff to very complex in a heartbeat, and they sometimes use a concept or command before it can be properly understood One example: Introducing the Unix commands head and tail, then moving on to split and csplit. The introduction to regular expressions as needed by csplit follows a few pages later.

Nevertheless, I plan to use this book as a companion text to my own sequence of computer classes for biologists, and I think it will serve that purpose very well.

Useful only for a reference book
We are all well aware that it is impossible to write a book on bioinformatics satisfying all types of readers. That is the reason why we are spending much time on finding a book that we can say "This book is just for me!"

Well, this book is not a self-teaching book by itself. Don't expect that things will become clear to understand after reading this book.

If your expectation is just to taste flavor of bioinformatics and to use it as a reference book, then this book is right for you.

Quite good introduction
This is a quite good book for people who have little background in Bioinformatics or Computer Science. I have to say it was pretty good in introducing basic ideas in Bioinformatics, and online resources.

However, I think the authors can do a better job in providing more details in certain areas, for example, in Perl programming, and in sequence alignment. Some parts of the book is so simple that the contents in those parts are not quite useful.

I would recommend this book to people who are new to Bioinformatics. But not to people who have taken one or two
introductory classes.

A Great Book For Exploring the Bioinformatics Field
It's no deep secret many Information Technology (IT) professionals today are facing a rough road finding gainful employment. In fact, according to Information Week, nearly 10% of the US IT workforce vanished in the last two months of 2002. More aptly put, some 272,530 American IT professionals in October were unemployed by December. This data is corroborated by the Bureau of Labor Statistics. Where did they all go? Many almost certainly got jobs in other professions and many still could be seeking employment. Employment counselors are encouraging IT professionals to "repurpose" those hard earned tech skills.

Bioinformatics is a ripe apple waiting to be eaten. Bioinformatics simply stated is the computational and analytical methods to biological problems. If this sounds like an open ended explanation, it is. In fact, according to O'Reilly's definitive publication on the topic, "Developing Bioinformatics Computer Skills" by Cynthia Gibas and Per Jambeck, there are several different definitions to Bioinformatics, but suffice to say all revolve around applying IT to the management of biological data.

Chapters one through six delineate the basics including the typical and common software and hardware requirements for Bioinformatics. I will tell you right now if you want to be successful in this fresh field, you must learn Unix. The book points out why. Unix is used extensively in universities and academia where the abundance of software for scientific data analysis is developed. Not to mention in the mid nineties, the only workstations able to visualize protein data structure in real-time were Silicon Graphics and Sun Unix workstations. Linux fans rejoice! As the book points out, "Linux is an excellent platform for developing software, so there's a rich library of tools available for computational biology and research in general."

Sound interesting? At this point you could be overwhelmed and ask yourself, "Where do I start?" Well, you may want to purchase O'Reilly's "Developing Bioinformatics Computer Skills" to see what the fuss is all about, determine whether you have what it takes to succeed in this new field, and most importantly, get an introduction to the software tools for biological applications from the inside out. Bioinformatics is a growing field that will continue for the unforeseeable future.

If you're serious about turning around that stagnant IT career and expanding your education, you may find yourself in the same enviable position you were three years ago...needed and wanted! But don't let me mislead you. As the book points out, Bioinformatics is first and foremost a biological science. ... Read more

Product Description
Mastering Perl for Bioinformatics covers the core Perl language and many of its module extensions, presenting them in the context of biological data and problems of pressing interest to the biological community.This book, along with Beginning Perl for Bioinformatics, forms a basic course in Perl programming.This second volume finishes the basic Perl tutorial material (references, complex data structures, object-oriented programming, use of modules--all presented in a biological context) and presents some advanced topics of considerable interest in bioinformatics. Biologists and computer scientists who have conquered the basics of Perl and are ready to move even further in their mastery of this versatile language will appreciate the author's well-balanced approach to applying Perl's analytical abilities to the field of bioinformatics. Full of practical examples and real-world biological problem solving, this book is a must for any reader wanting to move beyond beginner level Perl in bioinformatics. ... Read more

Customer Reviews (9)

Good starting material for programming perl in bioinformatics
Combined with the authors other book, Beginning Perl for Bioinformatics, this book provides a good self-study guide for those interested in understanding bioinformatics. This book is useful for biologist who has some programming experience, as well as programmers with some biology knowledge. It's written in a style that should suite most readers, as I find it each and smooth to read. Those looking for strict definitions or theory should look elsewhere.

Only chapters 4, 5 and 9 make it a worthwhile "Masters" book
This book is definitely written for the biologist that knows some perl and not the experienced perl programmer. To the biologists who have some experience, this book will open up many new possibilities, but to a person with a few years of perl experience, many sections are skimpy and wasteful on topics better covered by other Perl books.

For example, for anyone with truely massive datasets, it might have been worth the mention of the performance cost/benefits of using BerkleyDBs and hash joins (180-3500 times). With improvements of 2-3 orders of magnitude for large sets, it would have been worth a complementary example in chapter 6 so that readers can weigh the alternatives for certain situations.

The book, however, is well worth the price just for chapters 4, 5 and 9.

4) Sequence Formats and Inheritance
5) A Class for Restriction Enzymes
9) Introduction to Bioperl

A good follow-on to Tisdall's other Perl book
This book is a continuation of Tisdall's "Beginning Perl for Bioinformatics" and thus illustrates more advanced Perl programming techniques. This book not only talks about Perl programming, but it goes into some detail on the subject of bioinformatics itself. It is assumed that the CS-type reader has a good understanding of biology and the goals of bioinformatic programming. Otherwise, the examples and projects within the book will not make sense. The following is a description of the book's contents:

Part I: OBJECT-ORIENTED PROGRAMMING IN PERL
Chapter 1. Modular Programming with Perl - Talks about using modules so that other people can reuse your programs and you can reuse other people's modules in your own programs.

Chapter 2. Data Structures and String Algorithms - Talks about all of the different data structures available through Perl and how to build up special structures in Perl that you might need to describe complex data. Also mentions various string algorithms that are used in analyzing biological data and implements them in Perl.

Chapter 3. Object-Oriented Programming in Perl - Introduces object-orientation in Perl via a module that includes a class that keeps track of genes.

Chapter 4. Sequence Formats and Inheritance - How to convert sequence files into alternate formats such as FASTA and GCG. The object-oriented concept of inheritance is also introduced.

Chapter 5. A Class for Restriction Enzymes - By writing a more complex class, you get a bigger dose of object-orientated programming in biology.

Part II: PERL AND BIOINFORMATICS
Chapter 6. Perl and Relational Databases - Talks about SQL and the design of relational databases. MySQL is examined specifically.

Chapter 7. Perl and the Web - You learn about web programming in Perl by seeing how to put a laboratory on the Web via Perl and CGI.

Chapter 8. Perl and Graphics - Graphics programming in Perl is demonstrated when you learn to write a program that displays changing data to the Web. The graphical Perl module PD is discussed and demonstrated in a program.

Chapter 9. Introduction to Bioperl - Introduces the reader to Bioperl, which is a group of open source Perl modules used for bioinformatics programming. They provide many basic facilities so you don't have to worry about them.

Part III: Appendixes
Appendix A. Perl Summary
Appendix B. Installing Perl

I really thought this was a 5-star book. However, it is not obvious from the title that this is really volume two of a two volume set of books on Perl programming for the biologist, so I can see where the lower ratings might have come from.

Perhaps the CGI could have been omitted?
This is the sequel to his earlier beginner's book on Perl. Now, he goes further into usages of Perl. While experienced programmers will not find these terribly challenging, they are not the intended audience.

Of the topics, the most important is where he shows you how to interface with a SQL database. Given the sheer mass of sequence data generated these days, it is inevitable that efficient database usage be done. So he gives a quick tour of relational database design. With examples of how Perl has modules to submit and query the database. The treatment is somewhat cursory, since he has other, non-database topics to cover.

Of those, he includes CGI programming. This might be questionable. CGI code has proved incredibly hard to scale. Maybe he felt the necessity to include code for handling web servers. Unfortunately, a typical reader won't have enough experience to be aware of CGI's problems. The danger is that she actually starts coding CGI Perl. The true debugging and maintenance costs will not show up till later.

Good Companion text
This first half of the book focuses entirely on Object-Oriented(OO) Perl. The second half follows up with a general survey of various perl implementations of particular programming issues involving databasing, cgi, graphics, modules, etc, and BioPerl.

This book does a good job of applying Perl in OO for Biology in the first half of the book. In the second half he overviews a few broad topics in bioinformatics; he doesn't go super specific, but its a sufficient overview and for me sparked more interest in understanding how I can use perl to handle my informatics issues.

In the first half, the author does an excellent job on detailing the ins and outs of perl references and how to construct complex data structures. Indeed they are a bit strange looking at first, but the author breaks it down really good so pretty much anyone can understand it.

For me the most intriguing part of the book was in the second half, which included relational databases, graphics, and bioperl. In particular, the chapter that covers Perl DBI and DBD::mysql was really cool. That secion was very helpful for me because I am familiar with php/mysql, but have not ever used Perl to interact with Mysql before.

I especially liked the gif draw aka GD chapter. I had no idea how cool GD is. But moreover how it can be integrated with Perl to generate really cool looking plots. Before this book I always used gnuplot. But Tisdall shows you how to get to work with GD pretty good using basic practical examples.

The chapter on BioPerl was especially helpful as well. In particular, he shows you what he did to install the beast. He shows you how to use the CPAN shell and again its really beneficial to read through. It motivated me to pursue other topics in bioperl and how I can use it to query different ncbi databases for example.

Overall, the text provided a good overview on OO Perl and on various other topics involving Perl for Bioinformatics in general. I am glad I bought it. It was really very practical/useful - I refer to it all the time actually! ... Read more

Product Description

Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems.

Drawing on the author’s first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code.

With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

Customer Reviews (6)

Finally! The long missed book!
R itself is well equipped with documentation, which ships with every
distribution of R and the R add-on packages. But a good overall
picture, how R concrete is used in nowadays bioinformatics software
development, was always missing.

If you are interested in bioinformatics software developing, and you
aren't looking for a book which is just explaining how to do standard
biological data analysis within R, or how to solve statistical
problems whit R, but how to implement R-code for the biological
research field - this is the book! The book goes in a reasonable deep
through the whole guts of the R language and the core of the
bioconductor project. Detailed material can then always be found in
the substantial official documentation.
This book was written by a master wizard of the filed - Robert
Gentleman, R developer form the beginning on and member of the
[...] project core team.

Recently another book - R in a Nutshell, which promises to go through
the R guts in a same manner, was published by the famous O'Reilly.I
haven't read 'R in a Nutshell' yet, so I can't compare. However, to
bioinformaticians whit a programmer's angle I can warmly recommend 'R
Programming for Bioinformatics'. For me it was a pleasure to read. And
it remains one of the best guideline and source to start tackling R
software development challenges, in unfamiliarly and new informatics
fields.

Weak writing, poor editing, uncertain audience
The book is not designed to teach you R or programming and offers little about using R for bioinformatics (apparently Chapter 5, for "Working with Character Data", and Chapter 8, about "Data Technologies", account for the "bioinformatics" part). The text is riddled with writing errors -- the author writes badly in English, however expert he may be in R -- and looks as though it has not been copy-edited at all, with all the typos, extra words, misspellings, and awkward or wrong syntax. Concepts are not introduced sequentially or systematically defined; for one example (p43) "expr" is defined as "any valid R expression" -- but "expression" is never defined.

Chapter 3, on "Object-Oriented Programming in R", I find effectively unreadable. In 3.2 appears "Inheritance allows new classes to extend, often by adding new slots...". Aside from the misuse of the transitive verb and the dangling participle, the author nowhere bothers to define "slot", but continues to use it thereafter. If he had decided for whom he is writing the book and that it was an audience advanced enough to have used an OOP language, he might have said "In R, "slot" refers to what is called a "member" in Java or C++." Then he starts talking about "dispatch", only some time later casually "defining" it two or three times. The trouble with this approach is that you never work out what you're supposed to know already, and finally decide that the author himself doesn't know or care. It would be far better to have a book of which the first third is elementary, but systematic, lead-in that you can skip if sufficiently advanced, and the second two thirds is useful stuff that refers back to the earlier material.

Problems often do not draw on material that has been presented by example; they assume that you don't need the book and can go learn the language from the onscreen R help material. After several examples of this, I got to Ex. 2.21 on p66, where the reader is told to "produce a bitmap image of a plot", with not a single example of any graphics call leading up to this. In consequence of these disconnects, I gave up working the problems, which would ordinarily be the best way to learn the language. Tellingly, the last thing the author wrote before posing this series of graphics questions was "interested readers are encouraged to explore these different settings themselves." In other words, "Why read my book? Go find out for yourself!"

I program in several languages and teach one at the introductory level. I have trouble learning from this book even at my level and would have much more as a novice programmer. For such an important language and an author who's reputed to be one of the heavy hitters in the R community, this is disappointing.

Decent book
My only concern is that it at various stages the book feels like a programming book on S instead of on R. It needs better editing... content wise its decent & a good starting point!! Particularly god thing is that you don't have type in all the code when you are practicing, you can download written code from the CRAN website!!

Clearly written intro to R _programming_, not general use
The previous two reviewers are apparently frustrated because this book is not what they expected. In R world, however, _programming_ does not mean doing statistics or graphics in R - it means R software development. If the book was called "R Software Development for Bioinformatics", there would perhaps be less confusion - unless there was somebody who would be then led to believe that it was the book about developing core R software...

Anyway, this book is well organized and clearly written. As for bioinformatics, the author is not only a co-creator of R, he is a leading figure of the Bioconductor project. Suitable for a bioinformatics-oriented book, it has a whole big chapter on working with character data (not something discussed at great length in other R books, and a very useful chapter on Data Techniques replete with real-life Bioconductor examples. The chapter on OOP comes early in the book and, while does not go into too many details, it is enough to get you going sooner rather than later.


As a conclusion: potential buyers should be careful about whether the content of this book is what thy need. Those who do will probably be happy with the way it is written.

General R introduction, not for bioinformatics
I expected that this book is designed to introduce R programming for various works of bioinformatics with bunch of practical examples.
In short, this book is another R programming introduction book with no practical bioinformatics examples. I wonder why this book is for bioinformatics. This book is just for general R users, not especially for bioinformatics purpose. ... Read more

Product Description
Structural Bioinformatics was the first major effort to show the application of the principles and basic knowledge of the larger field of bioinformatics to questions focusing on macromolecular structure, such as the prediction of protein structure and how proteins carry out cellular functions, and how the application of bioinformatics to these life science issues can improve healthcare by accelerating drug discovery and development. Designed primarily as a reference, the first edition nevertheless saw widespread use as a textbook in graduate and undergraduate university courses dealing with the theories and associated algorithms, resources, and tools used in the analysis, prediction, and theoretical underpinnings of DNA, RNA, and proteins.

This new edition contains not only thorough updates of the advances in structural bioinformatics since publication of the first edition, but also features eleven new chapters dealing with frontier areas of high scientific impact, including: sampling and search techniques; use of mass spectrometry; genome functional annotation; and much more.

Offering detailed coverage for practitioners while remaining accessible to the novice, Structural Bioinformatics, Second Edition is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields.

Praise for the previous edition:

"This book is a gold mine of fundamental and practical information in an area not previously well represented in book form.” Biochemistry and Molecular Education

“... destined to become a classic reference work for workers at all levels in structural bioinformatics....recommended with great enthusiasm for educators, researchers, and graduate students.” BAMBED

"…a useful and timely summary of a rapidly expanding field." Nature Structural Biology

"...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue." Briefings in Bioinformatics  ... Read more

Customer Reviews (5)

Excellent book on structural biology and informatics
This book provides an excellent resource for anyone interested in structural biology and/or structural bioinformatics. One of the best structural biology related books I have read.The chapters are well organized and comprehensive, and I highly recommend this book. A+

A Legit review from a REAL: reader
Ok, there are 3 reviews listed here from what seems to be the authors or their closest friends... I give these about as much credit as whale dung at the bottom of the ocean.That being said, this *IS* an awesome summation of current knowledge in the fields of Structural biology and bioinformatics, especially for one with a working (undergraduate) knowledge of biological building blocks.
A few things of note:the book is aimed at biologists.This is not to imply that computer scientists or actuarial scientists will never understand this book, but rather implies that the approach to instruction is taken from the biological realm and then expanded to other related fields.
Also note that this is aimed strictly at comparative structural bioinformatics.While mentioned in the book, topics like transcription factors, x-ray crystalographic methods, or multi-cell signalling networks are best left for other books.This particular book, while touching on the subjects, does not go into much depth in these subjects.Personally, I feel this is all the better, allowing for a better primer of the subjects.
All in all, I have to say that this is one of the best books to date for an upper-undergraduate / graduate student to gain a working knowledge of Structural Bioinformatics.As such, I gladly rate this a 5 star book!

Terrific Book
"...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue." (Briefings in Bioinformatics)

Useful and Timely
"...a useful and timely summary of a rapidly expanding field." (Nature Structural Biology, Vol. 10, No. 8, August 2003)

Recommended Book
"...recommended for anyone who wishes to develop bioinformatics tools for protein structure analysis." (The Biotech Journal, April/May 2003) ... Read more

Product Description
Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, including BLAST, gene finding, and evolutionary inference, much of which has not yet been summarized in an introductory textbook format. This book grew out of a need to teach bioinformatics to graduate students at the University of Pennsylvania. At the same time however, it is organized to appeal to a wider audience. In particular it should appeal to any biologist or computer scientist who wants to know more about the statistical methods of the field, as well as to a trained statistician who wishes to become involved in bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, and will be accessible to students who have only had introductory calculus and linear algebra. Later chapters are immediately accessible to the trained statistician. Only a basic understanding of biological concepts is assumed, and all concepts are explained when used or can be understood from the context. Several chapters contain material independent of that in other chapters, so that the reader interested in certain areas can proceed directly to those areas. Warren Ewens is Professor of Biology at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics, and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceeding of the Royal Society B and SIAM Journal in Mathematical Biology. He was recently awarded the Gold Medal of the Australian Statistical Society and elected as Fellow of the Royal Society. His research interests are in evolutionary population genetics, linkage analysis for human diseases, and bioinformatics. Gregory Grant is a bioinformatics researcher at the University of Pennsylvania in the Computational Biology and Informatics Laboratory (CBIL), where he has been since 1998. In 1995 he received a Ph.D. in Mathematics from the University of Maryland and in 1999 a Masters in Computer Science from the University of Pennsylvania. His research interests are in bioinformatics in general and in particular in the statistical analysis of gene expression data and significance testing methods for IBD-mapping. ... Read more

Customer Reviews (4)

A good read, but only if you have adequate probability and statistics background
This is a useful book for people who have some background in probability and statistics to understand methods in bioinformatics. The chapter on BLAST theory is useful, as not too many books talk about it. Newcomers into the field who have absolutely no math background may find it hard to understand, though - definitely not a book for the beginner.

Digital library is not that usable - book itself is great
USUALLY I am very positive in my responses.But this gibberish:

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COPYRIGHTED MATERIAL
Warren J. Ewens, Gregory Grant. Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health). (Springer, 2005). Page 231.

is what you get when you (pay for) the digital copy and want to use your (secret number of) copy privileges.Your print privileges - to print out the page - are limited as well and you do not know ahead of time what that limit is. It seems to be 0. Which should not be sold as a print privilege.The annotations come out in this same weird encoding and the "Report a Problem" link has been irritating me since I first tried April 17 when I purchased this article. I wanted to report that the text is dim and fuzzy, very difficult for reading online, so I filled out the "Report a problem" form.I spent time filling it out. The response was that "We know this doesn't work and we are working on it and try again later".That was April 17.Still happening.There is no place to rate the digital service.

I gave up and wrote regular Amazon customer service.
Amazon customer service refunded the price of the digital subscription.

Lots of material made accessible
I'm a Statistics PhD student so you can condition on my prior to get at what's really going on with this book.

Bioinformatics is a departure from "regular" statistics and looks awfully messy at first pass.The sorts of assumptions one typically makes in other areas of statistical inference are patently false, so new techniques and intuitions have to be built up in order to attack these kinds of problems.This book does an excellent job of balancing the technical details with the necessary intuitions so one can really get a firm grasp on what's going on.

I wouldn't recommend this book to someone who hasn't done statistics at at least an advanced undergrad level (e.g., comfortable with Probability at the Ross-level and Statistical Inference at the Casella/Berger-level).But for people really interested in the material and coming from a solid statistical background the book is an excellent resource.

I would also strongly recommend it to teach out of.

Most Elegant Account of Bioinformatics
I was impressed with the 1st edition of this book for its most comprehensive and elegant of statistical techniques in bioinformatics. The book is slightly below the level of the now classic M S Waterman (1995)book:Introduction to Computational Biology: Maps, Sequences and Genomes (Interdisciplinary Statistics). But this book is more update in some areas and has much more background materials on probability and statistics, which should provide a solid basis for understanding bioinformatics. Its pedagorical sense is unparalleled. It would make a very good choice for a stat/math oriented introduction to bioinformatics (as opposed to algorithimc/database oriented approach in cs). ... Read more

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Praise from the reviews:

"Without reservation, I endorse this text as the best resource I've encountered that neatly introduces and summarizes many points I've learned through years of experience.  The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity." CIRCGENETICS

"This book may really help to get geneticists and bioinformaticians on 'speaking-terms'... contains some essential reading for almost any person working in the field of molecular genetics." EUROPEAN JOURNAL OF HUMAN GENETICS 

"... an excellent resource... this book should ensure that any researcher's skill base is maintained." GENETICAL RESEARCH

“… one of the best available and most accessible texts on bioinformatics and genetics in the postgenome age… The writing is clear, with succinct subsections within each chapter….Without reservation, I endorse this text as the best resource I’ve encountered that neatly introduces and summarizes many points I’ve learned through years of experience. The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity.”  CIRCULATION: CARDIOVASCULAR GENETICS

A fully revised version of the successful First Edition, this one-stop reference book enables all geneticists to improve the efficiency of their research.

The study of human genetics is moving into a challenging new era. New technologies and data resources such as the HapMap are enabling genome-wide studies, which could potentially identify most common genetic determinants of human health, disease and drug response. With these tremendous new data resources at hand, more than ever care is required in their use. Faced with the sheer volume of genetics and genomic data, bioinformatics is essential to avoid drowning true signal in noise. Considering these challenges, Bioinformatics for Geneticists, Second Edition works at multiple levels: firstly, for the occasional user who simply wants to extract or analyse specific data; secondly, at the level of the advanced user providing explanations of how and why a tool works and how it can be used to greatest effect. Finally experts from fields allied to genetics give insight into the best genomics tools and data to enhance a genetic experiment.

Hallmark Features of the Second Edition:

• Illustrates the value of bioinformatics as a constantly evolving avenue into novel approaches to study genetics
• The only book specifically addressing the bioinformatics needs of geneticists
• More than 50% of chapters are completely new contributions
• Dramatically revised content in core areas of gene and genomic characterisation, pathway analysis, SNP functional analysis and statistical genetics
• Focused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike

Bioinformatics for Geneticists, Second Edition describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. The book is based upon the combined practical experience of domain experts from academic and industrial research environments and is of interest to a broad audience, including students, researchers and clinicians working in the human genetics domain. ... Read more

Customer Reviews (1)

A Timely Primer for Researchers about the Analysis of Genetic Data
This book is a welcomed addition to the literature of bioinformatics. It helps one become familiar with how to find and use genetic data. This is a dauting task for most investigators who must navigate through the sea of genetic data now being produced. Analyzing genetic data is not an easy task but this book helps one identify resources and map a course. ... Read more

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Reviews of the Second Edition
"In this book, Andy Baxevanis and Francis Ouellette . . . have undertaken the difficult task of organizing the knowledge in this field in a logical progression and presenting it in a digestible form. And they have done an excellent job. This fine text will make a major impact on biological research and, in turn, on progress in biomedicine. We are all in their debt."
--Eric Lander, from the Foreword to the Second Edition
"The editors and the chapter authors of this book are to be applauded for providing biologists with lucid and comprehensive descriptions of essential topics in bioinformatics. This book is easy to read, highly informative, and certainly timely. It is most highly recommended for students and for established investigators alike, for anyone who needs to know how to access and use the information derived in and from genomic sequencing projects."
--Trends in Genetics
"It is an excellent general bioinformatics text and reference, perhaps even the best currently available . . . Congratulations to the authors, editors, and publisher for producing a weighty, authoritative, readable, and attractive book."
--Briefings in Bioinformatics
"This book, written by the top scientists in the field of bioinformatics, is the perfect choice for every molecular biology laboratory."
--The Quarterly Review of Biology
This fully revised version of a world-renowned bestseller provides readers with a practical guide covering the full scope of key concepts in bioinformatics, from databases to predictive and comparative algorithms. Using relevant biological examples, the book provides background on and strategies for using many of the most powerful and commonly used computational approaches for biological discovery. This Third Edition reinforces key concepts that have stood the test of time while making the reader aware of new and important developments in this fast-moving field. With a new full-color and enlarged page design, Bioinformatics, Third Edition offers the most readable, up-to-date, and thorough introduction to the field for biologists.
This new edition features:
* New chapters on genomic databases, predictive methods using RNA sequences, sequence polymorphisms, protein structure prediction, intermolecular interactions, and proteomic approaches for protein identification
* Detailed worked examples illustrating the strategic use of the concepts presented in each chapter, along with a collection of expanded,more rigorous problem sets suitable for classroom use
* Special topic boxes and appendices highlighting experimental strategies and advanced concepts
* Annotated reference lists, comprehensive lists of relevant Web resources, and an extensive glossary of commonly used terms in bioinformatics, genomics, and proteomics
Bioinformatics, Third Edition is essential reading for researchers, instructors, and students of all levels in molecular biology and bioinformatics, as well as for investigators involved in genomics, clinical research, proteomics, and computational biology. ... Read more

Customer Reviews (14)

Not a very useful textbook at all
I agree with the reviewer who said that this book is poorly organized.Actually, I would summarise this book with a single saying: TMI (Too Much Information)!In teaching you how to accomplish a simple task, the details given are tremendous, so much so that you can't see the forest from the trees and you end up having to navigate the bioinformatics Web sites by trial and error anyway.Perhaps this book would be useful for a post-doc or someone already very familiar with those sites and want to know how they work.For the student (undergrad through Master), I suggest picking up the short-n-sweet paperback 'Bioinformatics' by Westhead, Parish & Twyman instead.

Somewhat more than an out-of-date catalog of tools
The book is a collection of chapters by different authors addressing software tools for various problems: database search, multiple sequence alignment, gene prediction, protein structure prediction, etc.A big flaw is that all of the authors assume a different level of prior background and have rather different emphases.

I'd have to agree with the other reviewer that Chapters 1 & 17, which constitute 10% of the book, are wasted paper.No one in 2001 (when the book was published), let alone 2004, needs Chapter 1's lengthy explanation of what e-mail and web browsers are.And the perl program at the anticlimax of Chapter 17 was ... anticlimactic.

The book is to a great extent a catalog of available software tools.With the exception of the chapters on multiple alignment and phylogeny, the emphasis is on not on how the tools work but how to operate them -- to the of saying "at this URL there is a web page where you can either paste in your sequence or upload a file".The idea of invoking a program through a Unix command line is more than once presented as a truly daunting prospect.The authors generally do a good job of emphasizing that the programs are the beginning of analysis and not the end; the results must always be viewed somewhat skeptically with an expert eye.

If you're coming at the book as a biologist, you will probably find it to be a useful catalog of software, though undoubtedly dated by now.If you're coming at it from the informatics side, you're going to need some background... a book like Dwyer's, Setubal and Meidanis's, or Mount's will get you up to speed on the algorithm aspects of the field with simplified versions of many of the big problems.Then you can look at this book to find good pointers to the ways the real-world versions have been addressed.

The book was published three years ago and, being to a large extent an index of the work of others, is necessarily no longer up to date in a fast-moving field.It needs a revision and, in the meantime, it would make more sense to snag a used copy than to pay full price for a new book.

A survey for tool users
Like any survey, it seems to touch the major features only. And, as others have pointed out, the tools change but the book doesn't.

I think this is a good, brief introduction to the wide variety of bioinformatic tools and databases on the internet. It describes the major features of each, and the kinds of results that each tool is good for. After that, the serious user will go to the sources of each tool or database, to learn more about the specifics as of the moment. No book can hope to keep up with the weekly enhancements at the major repositories.

I emphasize that this is for tools users, not tool makers. It addresses the working scientists who already know their subjects and their needs. This skips over the algorithms in favor of higher level descriptions, and skips over many of the biological reasons for the tools described. Better-informed tool users get better answers from the tools, true. At some point, though, the biologists want to skip the theory, skip the introduction to subjects in which they're experts, and get on with their science. I don't think this book was ever meant for people - and I'm one - who want full details of the algorithms.

I agree, the book treats its many subjects in a shallow way. I think that is by intent, since the book's real goal is breadth and its target is a reader who knows the basic science. It's a bit off the center of my interests, but I've found it helpful.

Bioinformatic for the beginner...
I guess that everybody interrested by this kind of book knows already a little about bioinformatic and wants to improve his bioinformatician skill. So forget about this book:
This is really a well-documented introduction to all the methods currently used by every biologist or biology student, such as Blast, Clustal, multiple alignement or use of web-interface for submiting sequence.
So get it if you need a clear introduction to the field, but if you already know a little bit about bioinfo, immediately choose a more detailed book.

Poorly organized overpriced book
Although the book is presented as an introduction to the topic, its organization assumes that the reader has already been working in the area. Two of the chapters (1 and 17) are a waste of space. The first chapter presents a (useless) introduction to internet, while chapter 17 attempts (and fails to do so) to explain Perl in the context of bioinformatics. For the same money you can find far better books in the market. The good thing is that I only borrowed the book :) ... Read more

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Customer Reviews (3)

Good introductory book for learning both bioinformatics and pytho

Comparing to Perl, Python has a quite lagged adoption as the scripting language of choice in the field of bioinformatics, although it is getting some moment recently. If you read job descriptions for bioinformatics engineer or scientist positions a few year back, you barely saw Python mentioned, even as "nice to have optional skill".One of the reasons is probably lacking of good introductory level bioinformatics books in Python so there are, in general, less people thinking Python as a good choice for bioinformatics. The book "Beginning Perl for Bioinformatics" from O Reilly was published in 2001.Almost one decade later, we finally get the book "Bioinformatics Programming Using Python" from Mitchell Model to fill the gap.

When I first skimmed the book "Bioinformatics Programming Using Python", I got the impression that this book was more like "learning python using bioinformatics as examples" and felt a little bit disappointed as I was hoping for more advanced content.However, once I went through the book, reading the preface and everything else chapter by chapter, I understood the main target audiences that author had in mind and I thought the author did a great job in fulfilling the main purpose.

In modern biological research, scientists can easily generate large amount of data where Excel spreadsheets that most bench scientists use to process limiting amount of data is no longer an option.I personally believe that the new generation of biologists will have to learn how to process and manage large amount inhomogeneous data to make new discovery out of it.This requires general computational skill beyond just knowing how to use some special purpose applications that some software vendor can provide.The book gives good introduction about practical computational skills using Python to process bioinformatics data.The book is very well organized for a newbie who just wants to start to process the raw data their own and get into a process of learning-by-doing to become a Python programmer.

The book starts with an introduction on the primitive data types in Python and moves toward the flow controls and collection data type with emphasis on, not surprisingly, string processing and file parsing, two of most common tasks in bioinformatics. Then, the author introduces the object-oriented programming in Python. I think a beginner will also like those code templates for different patterns of data processing task in Chapter 4.They summarize the usual flow structure for common tasks very well.

After giving the basic concept of programming with Python, the author focuses on other utilities which are very useful for day-to-day work for gathering, extracting, and processing data from different data sources. For example, the author discusses about how to explore and organize files with Python in the OS level, using regular expression for extracting complicated text data file, XML processing, web programming for fetching online biological data and sharing data with a simple web server, and, of course, how to program Python to interact with a database. The deep knowledge of all of these topics might deserve their own books. The author does a good job to cover all these topics in a concise way. This will help people to know what can be done very easily with Python and, if they want, to learn any of those topic more from other resources.The final touch of the book is on structured graphics. This is very wise choice since the destiny of most of bioinformatics data is very likely to be some graphs used in presentations and for publishing.Again, there are many other Python packages can help scientists to generate nice graph, but the author focuses on one or two of them to show the readers how to do general some graphs with them and the reader might be able to learn something else from there.

One thing I hope the author can also cover, at least at a beginner level, is the numerical and statistical aspect in bioinformatics computing with Python.For example, Numpy or Scipy are very useful for processing large amount of data, generating statistics and evaluating significance of the results.They are very useful especially for processing large amount data where the native Python objects are no longer efficient enough.The numerical computation aspect in bioinformatics is basically lacking in the book.The other thing that might be desirable for such a book is to show that Python is a great tool for prototyping some algorithms in bioinformatics.This is probably my own personal bias, but I do think it is nice to show some basic bioinformatics algorithm implementations in python. This will help the readers to understand a little bit more about some of the common algorithms used in the field and to get a taste on a little bit more advanced programming.

Overall, I will not hesitate to recommend this book to any one who will like to start to process biological data on their own with Python. Moreover, it can actually serve as a good introductory book to Python regardless the main focus on bioinformatics examples. The book covers most day-to-day basic bioinformatics tasks and shows Python is a great tool for those tasks.I think a little more advanced topics, especially on basic numerical and statistical computation in the book, will also help the target audiences. Unfortunately, none of that topic is mentioned in the book. That has been said, even if you are an experienced python programmer in bioinformatics, the book's focus on Python 3 and a lot of useful templates might serve well as a quick reference if you are looking for something you do not have direct experience before.

Elegant guide that is desperately needed
The bioinformatics world badly needs this thorough and elegant guide
that applies Python's marvelously rich facilities to the domain of
biology.

A very good Book..!!
This book is really a great one for Bioinformatics programming. It is very easy to understand and very good examples are given in the book that are related to biological data. The content of the book is very well organized. All the topics are very well covered and explained. The biggest plus point of this book is that examples and data are picked very wisely which is really needed for Bioinformatics readers to understand well and to make their learning process easy and interesting. All the tables and examples, errors one might get while programming, screen shots of data extraction from database are very good and logical. I am sure this book will be admired by all biologists who want to learn Python and those who are familiar with Python and looking for a book to enhance their programing skills for querying Databases, extracting data from HTML, working with XML, URLs, OOL etc, This is the best book as it has covered everything with every single detail with an ease to understand the content. I Think this book will make Bioinformatics programmers life easier..!! ... Read more

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Collaborative research in bioinformatics and systems biology is a key element of modern biology and health research. This book highlights and provides access to many of the methods, environments, results and resources involved, including integral laboratory data generation and experimentation and clinical activities. Collaborative projects embody a research paradigm that connects many of the top scientists, institutions, their resources and research worldwide, resulting in first-class contributions to bioinformatics and systems biology. Central themes include describing processes and results in collaborative research projects using computational biology and providing a guide for researchers to access them.

The book is also a practical guide on how science is managed. It shows how collaborative researchers are putting results together in a way accessible to the entire biomedical community.

Product Description
There is an increasing need throughout the biomedical sciences for a greater understanding of knowledge-based systems and their application to genomic and proteomic research. This book discusses knowledge-based and statistical approaches, along with applications in bioinformatics and systems biology. The text emphasizes the integration of different methods for analysing and interpreting biomedical data. This, in turn, can lead to breakthrough biomolecular discoveries, with applications in personalized medicine.

Key Features:

• Explores the fundamentals and applications of knowledge-based and statistical approaches in bioinformatics and systems biology.
• Helps readers to interpret genomic, proteomic, and metabolomic data in understanding complex biological molecules and their interactions.
• Provides useful guidance on dealing with large datasets in knowledge bases, a common issue in bioinformatics.
• Written by leading international experts in this field.

Students, researchers, and industry professionals with a background in biomedical sciences, mathematics, statistics, or computer science will benefit from this book. It will also be useful for readers worldwide who want to master the application of bioinformatics to real-world situations and understand biological problems that motivate algorithms. ... Read more

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Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions

Developed from the author’s own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation and precisely defines the corresponding computational problems. He also includes detailed examples to illustrate each algorithm and end-of-chapter exercises for students to familiarize themselves with the topics. Supplementary material is available at http://www.comp.nus.edu.sg/~ksung/algo_in_bioinfo/

This classroom-tested textbook begins with basic molecular biology concepts. It then describes ways to measure sequence similarity, presents simple applications of the suffix tree, and discusses the problem of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of genome rearrangement, and the problem of motif finding. It also covers methods for predicting the secondary structure of RNA and for reconstructing the peptide sequence using mass spectrometry. The final chapter examines the computational problem related to population genetics.