Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins

Book Description

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.

Customer Reviews:

Somewhat more than an out-of-date catalog of tools.......2004-03-27

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.......2003-10-09

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..........2003-01-31

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.......2002-09-30

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 :)

..........2002-06-27

I used the Baxevanis volume in coursework at Johns Hopkins Biotechnology program...several of the chapter authors are associated with the school. There's no doubt that the editor and authors are experts in their fields, but the volume seems somewhat dated, and is disjointed. I found a couple of the chapters virtually unreadable. The real killer is the price. The book is GROSSLY overpriced...

Book Description

The science and practice of medicine has undergone a fundamental change as a result of large-scale genome projects that led to the sequencing of a number of important microbial, plant and animal genomes in the last 5 years. This book aims to combine industry standard software engineering and design principles, genomics and bioinformatics and cancer research. It focuses on creating and integrating practical, useful tools for the scientific community in the context of real-life, real-value biomedical problems that researchers face on a routine basis, rather than being just a didactic exercise in learning a programming platform. The book leverages technologies for molecular biology, genomics and bioinformatics and cancer research developed by the NIH, NCI-Center for Bioinformatics (NCICB), the National Center for Biotechnology Information (NCBI, a division of the National Library of Medicine (NLM) at the NIH) and Stanford University.

Ontologies for Bioinformatics (Computational Molecular Biology)

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Very lucid explanations
Excellent book of how we apply Ontology into real life application.
Title can mislead: Greater focus on methods than content of ontologies

Ontologies for Bioinformatics (Computational Molecular Biology)
Kenneth Baclawski , and Tianhua Niu
Manufacturer: The MIT Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0262025914

Book Description

Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies -- computer-readable, precise formulations of concepts (and the relationship among them) in a given field -- are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.

The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthesis that supports both styles of reasoning. They discuss Bayesian networks as a way of expressing uncertainty, describe data fusion, and propose that the World Wide Web can be extended to support reasoning with uncertainty. They call this inductive reasoning web the Bayesian web.

Customer Reviews:

Very lucid explanations.......2006-11-14

One of the most clearly written books I have found on the topic. I agree with a previous reviewer that some areas were not covered, but the ones that were are well described.

I would love to see a follow-on that reviews major ontology works in progress and explains when and how to use them and how to effectively map from one domain or specialty to another.

Excellent book of how we apply Ontology into real life application........2006-11-10

I have been working on Model Driven Architecture, Meta-data driven software, Modeling tools and Ontology for over 4 years. I have also implemented a suite of software supporting MDA and Ontologies. The material that this books covered just speaks my words out. Now, I can easily articulate my MDA/Ontology problems out with this book. Life is so easy with the help of a book which is in line of my work. Hooray!

Title can mislead: Greater focus on methods than content of ontologies.......2006-01-14

I was disappointed in this book in the lack of depth or breadth on a couple of key areas as follows:

Item 1 - It appeared to me that ontologies were not explained in sufficient detail to help "newbies" determine exactly why a specific ontology was created and the specific functions it is designed to support. I'm considering the UMLS to prototype a search engine because it is a compilation of a number of ontologies. However, this provides numerous options for subsetting the UMLS; for those relatively new to these ontologies it is not clear which ontology subsets are the most important (i.e., which play a pivotal or lesser role for my intended use). For example, I can include SNOMED and HL7 subsets, but do they provide redundant concepts for my needs and if so, in which areas? It is not practical for me to learn then all, so I was hoping to obtain this information from this book. Unfortunately I was unable to do so quickly and have to dig more on my own (which was the reason to buy the book.....).

Item 2 - I noticed a couple of areas that may be missing for those more interested in the tools and process of using ontologies. For example, I did not see the Protege and LexGrid tools for visualization, from Stanford and Mayo Clinic respectively, in the index (I had located them in prior web search). In a more general sense, as I've been working with ontologies more and more, I've noticed that platform selection and interoperability seem to be stumbling blocks. This topic was not a major focus in the book.

Due to the breadth and complexity of the platforms and tools needed to effectively use ontologies, and the complexity and size of the ontologies themselves, addressing both of these large subjects in sufficient detail in one book may be very difficult. Perhaps this is the reason that this book did not reach the 5 stars potential. Perhaps it would if it had addressed one or the other, but not both.

Perhaps if the description and title clarified the focus of the book, I would have gotten a better idea of the content before purchasing (and unfortunately, returning).

Keep in mind that I'm relatively new to using ontologies.

High Content Screening (Methods in Molecular Biology)

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High Content Screening (Methods in Molecular Biology)

Manufacturer: Humana Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 1588297314

Book Description

High content screening (HCS) was developed by Cellomics Inc. in the mid-1990s to address the need for a platform that could be used in the discovery-driven research and development required to understand the functions of genes and gene products at the level of the cell. High Content Screening: A Powerful Approach to Systems Cell Biology and Drug Discovery discusses its use as a high throughput platform to understand the functions of genes, RNA, proteins, and other cellular constituents at the level of the living cell.
High Content Screening is assembled to assist both existing users of HCS, as well as investigators considering the addition of a discovery-driven platform to their research and development activities. The chapters have been organized into sections that highlight the importance of integrating instrumentation, application software, reagents, and informatics. In addition, there is a combination of pure review chapters on key topics and specific methods chapters.
Written by a team of world leaders in the field, High Content Screening is essential reading for senior scientists, advanced lab technicians, as well as students/post-docs who wish to apply HCS in their research and development programs.

Computational Methods for SNPs and Haplotype Inference

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Computational Methods for SNPs and Haplotype Inference

Manufacturer: Springer
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Binding: Paperback

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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)

ASIN: 3540212493

Book Description

This book constitutes the post-proceedings of the DIMACS/RECOMB Satellite Workshop on Computational Methods for SNPs and Haplotype Inference held in Piscataway, NJ, USA, in November 2002.

The book presents ten revised full papers as well as abstracts of the remaining workshop papers. All relevant current issues in computational methods for SNP and haplotype analysis and their applications to disease associations are addressed.

Kernel Methods in Computational Biology (Computational Molecular Biology)

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Kernal Methods in Biology
diverse examples

Kernel Methods in Computational Biology (Computational Molecular Biology)

Manufacturer: The MIT Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0262195097

Book Description

Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. One branch of machine learning, kernel methods, lends itself particularly well to the difficult aspects of biological data, which include high dimensionality (as in microarray measurements), representation as discrete and structured data (as in DNA or amino acid sequences), and the need to combine heterogeneous sources of information. This book provides a detailed overview of current research in kernel methods and their applications to computational biology.

Following three introductory chapters -- an introduction to molecular and computational biology, a short review of kernel methods that focuses on intuitive concepts rather than technical details, and a detailed survey of recent applications of kernel methods in computational biology -- the book is divided into three sections that reflect three general trends in current research. The first part presents different ideas for the design of kernel functions specifically adapted to various biological data; the second part covers different approaches to learning from heterogeneous data; and the third part offers examples of successful applications of support vector machine methods.

Customer Reviews:

Kernal Methods in Biology.......2007-01-09

Good Book and useful for research and as a course work

diverse examples.......2006-07-05

The book is recognition of the fact that computational biology is only now starting to emerge as an important scientific discipline in its own right. The book addresses 2 audiences whose research intersects. One is those doing other computational work and who perhaps already use these kernel methods, and who are unaware of issues in biology that need to be studied. While the other is those already in computational biology, but who have never used kernel methods. Essentially, the early chapters address these needs.

Then the bulk of the book gives examples where kernel methods are already being used in computational biology. The diversity of the examples should prove inspiring to some readers.

The book also goes somewhat briefly into using support vector machines. If this interests you, try consulting "Support Vector Machines for Pattern Classification" by S Abe, Springer 2005, 1-85233-929-2. It has a fuller treatment of the idea.

Computational Methods in Molecular Biology (New Comprehensive Biochemistry)

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Brief glimpses of many topics
A terrific overview of the grand challenges
covers lots of practical topics, however rather superficial.

Computational Methods in Molecular Biology (New Comprehensive Biochemistry)

Manufacturer: Elsevier Science
ProductGroup: Book
Binding: Paperback

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ASIN: 0444502041

Book Description

Computational biology is a rapidly expanding field, and the number and variety of computational methods used for DNA and protein sequence analysis is growing every day. These algorithms are extremely valuable to biotechnology companies and to researchers and teachers in universities.

This book explains the latest computer technology for analyzing DNA, RNA, and protein sequences. Clear and easy to follow, designed specifically for the non-computer scientist, it will help biologists make better choices on which algorithm to use. New techniques and demonstrations are elucidated, as are state-of-the-art problems, and more advanced material on the latest algorithms.

The primary audience for this volume are molecular biologists working either in biotechnology companies or academic research environments, individual researchers and the institutions they work for, and students. Any biologist who relies on computers should want this book.

A secondary audience will be computer scientists developing techniques with applications in biology.

An excellent reference for leading techniques, it will also help introduce computer scientists to the biology problems. This is an outstanding work which will be ideal for the increasing number of scientists moving into computational biology.

Customer Reviews:

Brief glimpses of many topics.......2003-10-10

I think the book is more about bioinformatics than molecular biology, but good anyway. If a student has already made some headway in bioinformatics, she is likely to want a peek at the different directions and depths that future study will offer. This book gives a good preview.

Its fifteen chapters are almost all by different authors, on different topics, in different styles and with different mathematical tools. Except for some introductory material, each chapter stands by itself. The chapters are uniformly well written, they keep their computations close to the biology, and they offer depth without falling into a morass of detail. The book uses math but is not too demanding; readers should not be put off by its "Computational" title.

Once inside the book, its authors take us on a quick tour of selected topics, including RNA splicing, high-level annotation of DNA meaning, and several views of protein structure. Computational techniques include traditional decision trees, as well as more modern hidden Markov model techniques, neural nets, analogy to vison processing, and much more.

This book presupposes a bit of knowledge of biology, chemistry, and probability, but not daunting amounts. It's a nice way for the beginner to see which directions look most personally interesting. It may also give the more focussed student a quick look at current highlights in nearby fields. This isn't as complete as a 'survey' book would be, but very good in its own way.

(I've had the pleasure of studying under Prof. Kasif, one of the editors and authors, and hope that familiarity has not prejudiced this review.)

A terrific overview of the grand challenges.......2002-01-15

This book offers a wonderful overview of the computational problems in bioinformatics. Readers with an interest in Artificial Intelligence / Machine Learning will find this book especially worthwhile. There are chapters on hidden Markov models, case-based reasoning, neural networks, evolutionary approaches (Genetic Algorithms), decision-trees, and probabilistic networks, among others. The book covers sequence analysis, gene prediction and annotation, and includes extensive material on protein structure prediction. A must read for anyone interested in Bioinformatics research.

In the interest of full disclosure, I want to mention that one of the editors of this book, Dr. Steven Salzberg, was my graduate advisor when I was a student at Johns Hopkins from 1992 to 1994.

covers lots of practical topics, however rather superficial........2001-01-29

This book is introductory. It deals with many topics such as biological sequence analysis, hidden markov model(HMM), gene prediction using Neural Networks, RNA splicing signal model, evolutionary approach and protein structure modeling. It is helpful to glimpse a broad overview of these topics, however the explanations are rather superficial. Especially the chapters covering sequence analysis are too concise.

In this respect, I recommend the following two books for the readers who want more clear and indepth explanations on the sequence analysis.

by Joao Carlos Setubal (Contributor), Joao Meidanis, Joao C. Setabal

by Richard Durbin (Editor), S. Eddy, A. Krogh, G. Mitchison (Contributor)

Also for the readers who are interested in bioinformatics tools, I would recommend

by Andreas Baxevanis (Editor), B.F.Francis Ouellette (Editor)

Book Description

This special volume collects invited articles by participants of the Third International Workshop on Methods for Macromolecular Modeling, Courant Institute of Mathematical Sciences, Oct. 12-14, 2000. Leading developers of methods for biomolecular simulations review advances in Monte Carlo and molecular dynamics methods, free energy computational methods, fast electrostatics (particle-mesh Ewald and fast multipole methods), mathematics, and molecular neurobiology, nucleic acid simulations, enzyme reactions, and other essential applications in biomolecular simulations. A Perspectives article by the editors assesses the directions and impact of macromolecular modeling research, including genomics and proteomics. These reviews and original papers by applied mathematicians, theoretical chemists, biomedical researchers, and physicists are of interest to interdisciplinary research students, developers and users of biomolecular methods in academia and industry.

Bioinformatics Research and Applications: Third International Symposium,ISBRA 2007, Atlanta, GA, USA, May 7-10, 2007, Proceedings (Lecture Notes in Computer Science)

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Bioinformatics Research and Applications: Third International Symposium,ISBRA 2007, Atlanta, GA, USA, May 7-10, 2007, Proceedings (Lecture Notes in Computer Science)

Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

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ASIN: 3540720308

Book Description

This book constitutes the refereed proceedings of the Third International Symposium on Bioinformatics Research and Applications, ISBRA 2007, held in Atlanta, GA, USA in May 2007.

The 55 revised full papers presented together with 3 invited talks were carefully reviewed and selected from a total of 146 submissions. The papers cover a wide range of topics, including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools.

Clinical Proteomics: Methods and Protocols (Methods in Molecular Biology)

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Clinical Proteomics: Methods and Protocols (Methods in Molecular Biology)

Manufacturer: Humana Press
ProductGroup: Book
Binding: Hardcover

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Book Description

The field of clinical proteomics has rapidly evolved during the past few years and is continuously growing as new methodologies and technologies emerge. In Clinical Proteomics, a select group of leading researchers has contributed their state-of-the-art methodologies on protein profiling and identification of disease biomarkers in tissues, microdissected cells and body fluids. Experimental approaches involving the application of two-dimensional electrophoresis, multi-dimensional liquid chromatography, SELDI/MALDI mass spectrometry and protein arrays, as well as the bioinformatic and statistical tools pertinent to the analysis of proteomics data, are thoroughly detailed in these readily reproducible methods and protocols, explained through the step-by-step instructional format of the highly successful Methods in Molecular Biology™ series.

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