Customer Reviews (2)

good general overview, introduction
This book provides a good general overview/introduction of bioinformatics, genomics and proteomics. It does assume, however, that the reader has at least an introductory background in biology and chemistry. If this is not the case, you will probably find this book too advanced.

I liked all of the websites and recommended readings for additional information as the Internet is sometimes a pain to search, so it is nice to have some good site recommendations. The chapters are concise and written well, but again, if you haven't studied these subjects before, I think the book will go over your head. All in all a good general overview for the beginning scientist- aka high-school level or intro college level.

First contact
If you don't know anything about Bioinformaticas, this book is very adeccuacy for your first time ... Read more

Product Description

The many books that have been published on bioinformatics tend toward either of two extremes: those that feature computational details with a great deal of mathematics, for computational scientists and mathematicians; and those that treat bioinformatics as a giant black box, for biologists. This is the first book using comprehensive numerical illustration of mathematical techniques and computational algorithms used in bioinformatics that converts molecular data into organized biological knowledge.

Product Description

Bioinformatics as a discipline has come of age, and there are now numerous databases and tools that are widely used by researchers in the biomedical field. However, successful development of future bioinformatics applications will depend on an appropriately formalised representation of domain knowledge.

This book provides a timely and first-of-its-kind collection of contributed chapters on anatomy ontologies. It is interdisciplinary in its approach, bringing together relevant expertise from computing and biomedical studies, and covering both theoretical and applied aspects, with an emphasis on newer work relevant to the emerging Semantic Web.

Topics and Features:

• Provides a comprehensive discussion of the foundations of anatomical ontologies and the state of the art in existing computational tools and applications

• Considers a number of fundamental modelling principles

• Includes chapters about research on algorithms to systematically align anatomy ontologies and to mine data in the literature, using anatomy terms

• Explains recent efforts to develop a common anatomy reference ontology

• Discusses anatomy in the context of spatio-temporal biomedical atlases

• Describes systems and tools for linking anatomy ontologies with each other and with other on-line resources, such as the biomedical literature

• Highlights the challenges of dealing with anatomy-based information on the Semantic Web

Although primarily written for readers who will be involved in developing the next generation of IT applications in the areas of life sciences, biomedical sciences and health care, this unique volume will be of interest to anyone who will further develop anatomy ontologies, who will use them, and who will be involved in the actual development of relevant (semantic) web applications.

Product Description
“… this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues—making the book enticing and useful, all at once…” Human Vaccines, 2010

"... This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies... This book may well serve as a first line of reference for all biologists and computer scientists..." –Virology Journal, 2009

Vaccines have probably saved more lives and reduced suffering in a greater number of people than any other medical intervention in human history, succeeding in eradicating smallpox and significantly reducing the mortality and incidence of other diseases. However, with the emergence of diseases such as SARS and the threat of biological warfare, vaccination has once again become a topic of major interest in public health. 

Vaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. 

This is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development by

• introducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinology
• putting it into a historical and societal context, and 
• exploring the scope of its methods and applications.

Bioinformatics for Vaccinology is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices. ... Read more

Customer Reviews (2)

Weird and not exactly cohesive, but I like it
I work in this very field (bioinformatics and vaccinology), so I expect that I am right in the middle of this book's target audience.My impressions overall have been mixed, but at the end of the day I think this book is very good.The copy I had read came from a colleague, but I like it enough that I'll be buying a copy for myself.

This book is all over the place in ways that are good (even great) and bad.My initial reaction to this book was surprise:the first 50 pages was about the history of vaccination, followed by another 20 pages about the contemporary use of vaccines.So right there, 25% of the book is a historical and contemporary background -- a perspective neither technical nor heavily biological, as the title would otherwise imply.

At this point -- even though I was enjoying the material -- I felt that the title was misleading.And yet it still took another 40 pages of immunological background before Flower really kicks into the meat of the text.Here, however, is where the book turns into a terrific overview.I learned heaps -- about databases and analytical methods that I didn't even know existed.I was able to apply topics from the book immediately into my work, and I'm sure I'll reference it again in the future.It's like a terrific survey course.It won't teach you how to program, or model databases, or analyze data, or how to use any of the tools/methods that are discussed, but it gives you a nice scenic tour of all the important landmarks you should know about.

I mentioned that my reaction was mixed, and indeed this book has some downsides worth mentioning.The largest is that the author never properly settled on who the audience should be.It seems to me that the book is mostly geared toward graduate students or professional practitioners in molecular biology who want to learn about how developments in bioinformatics can expand their research horizons.(I.e., those people who are heavy on the bio-, light on the -informatics.)This is because the book itself is technically light.Still, the book features a bizarre, inconsistent mix of pedagogical background and assumed knowledge.

I mentioned previously that there are 40 pages of background about how vaccines and the immune system works, written at a good depth for the biologically-naive.Yet much of the successive content is seriously biobabble-rich, perfectly suited for any molbio Ph.D. candidate.For example (to pick a sentence at random):"The molecule may exist as a canonical ensemble of tautomers, thus necessitating the the explicit construction of all tautomeric forms."If you don't know what tautomers are, or why this statement might be important, don't look for an explanation in this book.And this was a frequent occurrence with me:I would come across some content that was out of my biological depth, then glaze over it and move on.This happened at least once per page, and on a few occasions entire pages-long sections were skipped.

(From the other perspective, there are methods and tools described in the text that strict biologists would probably regard as out of their depth if they were to try to implement them, although I suspect that they would find the descriptions easier reading, as this book wasn't as infused with technobabble or mathbabble.)

And here's a personal gripe:some references aren't fully cited, which is a shame for an overview like this.For example, the table of z-scales on page 195 only covers 18 of 20 amino acids, so I tried to find the table via the original source.The text only references "Svante Wold and coworkers" and didn't cite an actual paper.And unfortunately, due to the long and many-storied history of Wold's z-scales, it took a while for me to track down the specific paper that contained the most-recent version of the table.So I find it ironic:the purpose of the book is to provide a sampler of methods and tools to use in the field of computational vaccinology, but here I was, trying to implement one of the described methods, and there was a surprisingly large barrier in accomplishing it due to an inadequate amount of information.

Still, in spite of its weaknesses, I like this book a lot, for what it is:an overview for people who are already fairly entrenched in the field.You'll probably find the information more consistently enriching if you have at least some graduate-level exposure to biology, although if you work more on the computational side, just snooze through the biobabble and you should find some great nuggets in this book as well.

No better book on the subject exists
The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues. Full review can be found at - Hum Vaccin. 2010 May 23;6(5). ... Read more

Product Description
Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and its problem-solving capabilities are generally not yet understood or applied in the biology community.

This book offers a definitive resource to bridge the computer science and biology communities. Gary Fogel and David Corne, well-known representatives of these fields, introduce biology and bioinformatics to computer scientists, and evolutionary computation to biologists and computer scientists unfamiliar with these techniques. The fourteen chapters that follow are written by leading computer scientists and biologists who examine successful applications of evolutionary computation to various problems in the biological sciences.

* Describes applications of EC to bioinformatics in a wide variety of areas including DNA sequencing, protein folding, gene and protein classification, drug targeting, drug design, data mining of biological databases, and biodata visualization.
* Offers industrial and academic researchers in computer science, biology, and bioinformatics an important resource for applying evolutionary computation.
* Includes a detailed appendix of biological data resources. ... Read more

Customer Reviews (2)

Significant Addition to Biocomputing
I like this book. Bioinformatics is a ripe area for applying evolutionary algorithms and the book provides a good overview of many different applications. Some chapters are more polished than others, but that's to be expected. The editors do an excellent job of introducing both bioinformatics and evolutionary computation to their respective audiences. I can't think of another book that makes such an effort to integrate the two communities.

I see another reviewer gave the book 3 stars. I've no idea why. The book is excellent, and has encouraged me to take a look at other papers in this area.

A good literature survey
The subject of this book would seem a natural one, given the evolutionary paradigm in biology. Genetic algorithms and evolutionary programming have now found use in many different fields such as physics, financial engineering, network modeling, and computational radiology, to name a few. This use will no doubt continue as computer processing power increases in the future. Although genetic/evolutionary approaches are still much more effective from a computational point of view than strict combinatorial ones, they are still very time intensive, and for many problems have yet to compete with ordinary Monte Carlo techniques. This book gives a brief overview of how evolutionary algorithms are used in bioinformatics, with emphasis on genetic sequence alignment and protein folding. The book does not offer in-depth discussion on these algorithms, but does give references where more information can be obtained. Therefore the book could be described as a literature survey, at least for the chapters that I read, which did not include those on protein folding.

The book is written for the computer scientist who wants to move into bioinformatics, and the biologist, who needs more background in these types of algorithms. Therefore, the editors of the book include two introductory chapters, one introducing bioinformatics for computer scientists, the other an introduction to evolutionary computation for biologists. The latter is more detailed, and the authors introduce the biologist to some of the elementary aspects of evolutionary computation. One interesting, but too short discussion is on the "No Free Lunch Theorem", which implies that evolutionary programs are not in any sense "universal", in that the choice of such a program will depend on the problem at hand, and in fact there may be many such programs for the problem, each with their own performance properties. The theorem is not proved in this book, but references to the proof are given. However, the proof involves a level of mathematics that a biologist would probably not have knowledge of, and so this reference would not be accessible to such a reader. In addition, the theorem has generated a lot of controversy, but the authors do point this out. The authors also discuss effectively the difference between the analytical and heuristic approaches to sequence alignment, setting the stage for later chapters in the book. The problem of local search algorithms getting "trapped" in local minima is also given a very intuitive and understandable treatment by the authors.

The book also includes a discussion on the "DNA sequence reconstruction problem". Algorithms for dealing with this problem are recommended and the the problem is presented as one in integer programming. The authors present a hybrid evolutionary algorithm for dealing with this problem. They characterize this algorithm as being hybrid since it does make use of "crossover" operators and a heuristic "greedy-improvement" method. The discussion of this algorithm is only brief, but references are given. However the main reference is not yet available as it is very recent and in press, and, although the authors do include a fairly lengthy discussion of computational experiments, without a detailed description of the algorithm or source code, their results cannot be checked or validated.

The contrast between optimization theory and evolutionary algorithms is a common theme in the book, with emphasis on the use of evolutionary algorithms to design scoring schemes for sequence alignment where optimization issues can be ignored. The difference between the optimal alignment obtained by various mathematical techniques and the correct (biological) alignment is carefully pointed out. Thus one must be able to tell whether an objective function is relevant from a biological standpoint. In chapter 5 of the book for example, the author introduces an alignment algorithm based on a combination of simulated annealing (SA), and genetic algorithms (GA), called appropriately SAGA. This chapter is the most helpful one in the book, for the author gives pseudocode for this algorithm, with Web links given for obtaining the source code. This allows the interested reader to study the efficacy of the SAGA algorithm in doing muliple sequence alignment.

The use of simulated evolution to find optimal neural networks for identifying coding regions is discussed in chapter 9 of the book. The use of genetic algorithms to assign the weights in a neural network is well-known. The authors point out a further advantage in their use, namely that evolutionary neural networks can adapt to unexpected inputs on their own, and thus do not require any intervention on the part of the user. References are given that elaborate on the power of this approach. Readers who have worked with neural networks will understand fully the need for improvements over back-propagation and the need for automatic topology selection. The authors do not show however that the function-approximation ability of neural networks, so important from both a mathematical and applications standpoint, is improved by their approach. ... Read more

Product Description
An emerging, ever-evolving branch of science, bioinformatics has paved the way for the explosive growth in the distribution of biological information to a variety of biological databases, including the National Center for Biotechnology Information. For growth to continue in this field, biologists must obtain basic computer skills while computer specialists must possess a fundamental understanding of biological problems. Bridging the gap between biology and computer science, Bioinformatics: A Practical Approach assimilates current bioinformatics knowledge and tools relevant to the omics age into one cohesive, concise, and self-contained volume.

Written by expert contributors from around the world, this practical book presents the most state-of-the-art bioinformatics applications. The first part focuses on genome analysis, common DNA analysis tools, phylogenetics analysis, and SNP and haplotype analysis. After chapters on microarray, SAGE, regulation of gene expression, miRNA, and siRNA, the book presents widely applied programs and tools in proteome analysis, protein sequences, protein functions, and functional annotation of proteins in murine models. The last part introduces the programming languages used in biology, website and database design, and the interchange of data between Microsoft Excel and Access.

Keeping complex mathematical deductions and jargon to a minimum, this accessible book offers both the theoretical underpinnings and practical applications of bioinformatics. ... Read more

Product Description

The problem many microbiologists face is simply that of too much information. This book details many published methods for comparison of genomes, and provides examples of how custom comparisons can be made. The choice of methods obviously depends on the questions to be asked, and of course on the quantity of genomes to be compared. Two similar bacterial chromosomes can simply be aligned with each other, and regions of inversions and deletions can be readily visualised. However, this method won’t work to compare hundreds of genomes, where 2-Dimensional clustering heat maps would be useful.

This text is built around teaching COMPUTATIONAL / BIOINFORMATIC methods for comparison of microbial genomes, and includes detailed examples of how to compare them at the level of DNA, RNA, and protein, in terms of structural / functional analysis.

Aimed at advanced undergraduate and graduate students in Bioinformatics and Microbiology, this book will prove an invaluable reference to computational and bioinformatics tools.

Product Description
Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research. ... Read more

Product Description
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies. ... Read more

Product Description
Bioinformatics: Methods Express is unique . It is a book on bioinformatics that makes sense to non-bioinformaticians.

Bioinformatics: Methods Express helps you answer common questions such as:

*what else is similar to my gene?
*does this protein have any transmembrane regions?
*how do I visualize an alignment between these DNAs?
*where can I find specific transcription factor sequences?

The book provides the clear advice and explicit protocols that non-bioinformaticians need in order to understand what to do - and how to avoid common pitfalls. Each chapter guides you through the major databases and tools with worked examples - all accompanied by sample data files available online.

Topics covered include:
*data access
*sequence searches and alignments
*identification and annotation of features
*the transcriptome
*protein structure and function
*comparisons and phylogeny

Bioinformatics: Methods Express is a comprehensive manual for all wet-bench scientists who need to use bioinformatics - from postgraduate student to principal investigator. ... Read more

Product Description

For decades, bioinformatics textbooks have primarily served gene-hunters and biologists constructing family trees showing tidy lines of descent. Written to make the ‘new’ information-based bioinformatics intelligible to both the ‘bio’ and the ‘info’ audiences, this book identifies the types of information that genomes transmit, shows how competition between different types is resolved in the genomes of different organisms, and identifies the evolutionary forces involved. Early chapters relate the form of information with which we are most familiar, namely written texts, to the DNA text that is our genome. Providing a pathway for introducing historical aspects dating back to the nineteenth century.

Product Description
Bioinformatics provides in depth coverage of the principles and applications of bioinformatic analyses of nucleic acid and protein sequences, databases and data mining. Dynamic programming algorithms of Needleman-Wunsch and Smith-Waterman, amino acid exchange matrices such as Dayhoff PAM series matrices and BLOSSUM series matrices and DOT matrix are discussed in detail along with pair-wise sequence alignment tools such as BLAST, FASTA and their variants, multiple sequence alignment tools such as CLUSTAL-W, CLUSTAL-X, SAGA, and progressive alignment and profile alignment. The book describes methods of detection and prediction of genes, ORFs, promoters, motifs, mRNA, tRNA, miRNA, their structure and function and protein structure and function using ab initio HMM and Neural Networks. Software programs like GeneID, Genescan, Genie, GeneModeler, GRAIL and GeneMARK for gene detection and visual mining tools available are discussed while Gene Ontology (GO) and use of sequence information for phylogenetic inferences are illustrated. ... Read more

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The Beauty of Protein Structures and the Mathematics behind Structural Bioinformatics
Providing the framework for a one-semester undergraduate course, Structural Bioinformatics: An Algorithmic Approach shows how to apply key algorithms to solve problems related to macromolecular structure.

Helps Students Go Further in Their Study of Structural Biology
Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in a 3D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design.

At the Crossroads of Biology, Mathematics, and Computer Science
Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).

Customer Reviews (2)

For whom is this intended?
This book does a good job of explaining the common algorithms used in Structural bioinformatics. The reason why I am not giving it more than 3 stars is because this kind of information isn't very useful to many people. Most of these algorithms have been realized by various programmers, and it is all available in many servers. There are several internet sites and freely downloadble programs where you can upload/input PDB files and do various things like calculate Ramachandran plots, align structures, calculate RMSDs between various structures, do structural classifications, look for novel folds, calculate surface areas, determine the interactions between proteins in complexes and several other things structural bioinformaticians normally do. This book is useful for people who want to develop programs which can do all the aforementioned. But why would anyone, other than pastime codewriters, want to do something that has already been done several times before?

good start for students
I find the book by Forbes J.Burkowski to be a good text for students with some programming skills. Instead of focusing on the vast array of bioinformatics tools available in this field, the author chooses to show the details of a few fundamental algorithms that are behind many of those tools. I think this is an efficient way of teaching serious, critical users and also future developers. However, the book is not as comprehensive as I expected as it misses important bits such as side-chain design or fold recognition algorithms. Nevertheless, reading this book will help you grasp these absent subjects more easily, and I guess that might have been the author's intention. ... Read more

Product Description
The technologies in data mining have been successfully applied to bioinformatics research in the past few years, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays an essential role in understanding the emerging problems in genomics, proteomics, and systems biology.

Advanced Data Mining Technologies in Bioinformatics covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. Advanced Data Mining Technologies in Bioinformatics is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic. ... Read more

Product Description
This book is an excellent introductory text describing the use of bioinformatics to analyze genomic and post-genomic data. It has been translated from the original popular French edition, which was based on a course taught at the well-respected École Polytechnique in Palaiseau. This edition has been fully revised and updated by the authors.

After a brief introduction to gene structure and sequence determination, it describes the techniques used to identify genes, their protein-coding sequences and regulatory regions. The book discusses the methodology of comparative genomics, using information from different organisms to deduce information about unknown sequences. There is a comprehensive chapter on structure prediction, covering both RNA and protein. Finally, the book describes the complex networks of RNA and protein that exist within the cell and their interactions, ending with a discussion of the simulation approaches that can be used to model these networks.

Praise from the reviews:

“In context of the new developments the genomic era has brought, Bioinformatics: Genomics and Post-Genomics becomes a fundamental and indispensable resource for undergraduate and early graduate students…insightfully authored…will immensely help students…in establishing important foundations while shaping their careers.” NEWSLETTER, BRITISH SOCIETY OF CELL BIOLOGY ... Read more

Customer Reviews (1)

Good introduction
This book is basically used for a bioinformatics class in France and translated in English. I've been working on developing tools for ncRNA gene predictions and this book clarifies of the mystery in genomics what I could not reach by biology books. Using pictures and figures, it's a pretty much comprehensive book.If you are a novice in bioinformatics field, I would recommend reading this book. However, if you expect to learn something in more specific such as machine learning or etc., then you may bedisappointed. ... Read more

Product Description
The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management. ... Read more

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Product Description
Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology

This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers:

• General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms

• Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding

• Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data

• Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies

• Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions

Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike. ... Read more

Product Description

This monograph addresses, in a systematic and pedagogical manner, the mathematical methods and the algorithms required to deal with the molecularly based problems of bioinformatics. Prominent attention is given to pair-wise and multiple sequence alignment algorithms, stochastic models of mutations, modulus structure theory and protein configuration analysis. Strong links to the molecular structures of proteins, DNA and other biomolecules and their analyses are developed.