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
Completely revised and updated, this new edition of a bestseller will continue to serve as a tool that allows researchers to easily access and use databases to gather information on genes, proteins, and diseases. It covers new approaches to data analysis using databases around the world. It identifies computing techniques that help readers manage the massive flow of information. The structure of this second edition will follow that of the first and its content will reflect the growth in information. New sections cover recent developments in genome projects, microarray, proteonics, brain mapping, and more. ... Read more

Customer Reviews (5)

I liked it but it could use more sample problems
I wanted to learn something about informatics...The book was easy to understand but it lacked practice problems... This is not a religious book...Obviously the book takes an evolutionary stand point since the entire concept of bioinformatics is based mainly on evolutionary similarities of proteins and other cellular components. If you are new to bioinformatics but have some understanding of Biology, then you should get this book...

An expensive hodgepodge
Books about bioinformatics are as diverse as the field itself. It may not be possible to do justice to this new and exciting field in 168 pages. My concern with this book, however, lies not with the choice of topics, but rather with its incoherent presentation. Distracting parenthetical remarks pervade the text as in this excerpt from the beginning of the 3rd chapter:"DNA sequences are often found based on predictive tools, meaning that sequence similarities of newly discovered genes yield information about their physiological functions and structures, PCR (polymerase chain reaction), finding sequence fragments of significance (how is significance judged? By predictive biology, once again), finding distribution of genes or mRNAs (often an indicator of gene activity in an organism), and amplifying the amount of DNA for purification, sequencing, and mutational analysis." (p. 143).

Chapter 5 entitled "The Computer Revolution in Neurobiology" we find the following unexpected text: "One rationale for human cloning is that it could alleviate many of the problems associated with our unique characteristics. The genetic information (DNA) of a cloned organ is identical to that of the individual needing the organ. Hence, the cloned organ would be accepted by the individual's body as part of itself and would have a smaller probability of rejection." (p. 159). [Nevermind the enormous ethical implications!]

Throughout, one has the sense of a book rushed to market to take advantage of an exciting scientific trend. The book presents nothing that can't be found on-line and it gives readers no sense of the computational challenges of the field. ...

I own this title in my library and is well worth the money!
I am a novice in bioinformatics and have found this book to be invaluable in getting me started without intimidating me. I have owned the book for over a year and still find it very useful but I am waiting for an update to this title soon since I have enjoyed the organization of the book. It has given me a global picture of informatics and chapters with specific examples and applications. I am sure a second edition to this book will be well recieved by the audience and I am hoping to see it soon since the new bioinformatics book I have just purchased is not to my liking.

Solid starting place for a novice
I'm always looking for a good guide book for undergrads and biocomputing novices that covers the basics without getting carried away with algorithmic minutiae. I found this book a fair place to start for those who have no idea of what is out there. The tools and Web sites described are mainstays and likely won't be going anywhere. However, if you are already moderately knowledgeable, you will exhaust this book immediately. The nature of the field is constant movement toward newer and more thorough tools. This is not a users' guide: go to the referenced Web sites themselves to get the most up to date, accurate information.

I would refer a naive beginner to get this book at the library, but I wouldn't put it on my own shelf.

Bioinformatics to the max!
This is truly a great book.I had always wondered about biological research and the use of computers.The future of medicine and mankind will be changed drastically by new advances created by the coupling of scienceand technology.Bioinformatics is the wave of the future and Rashidi showsin his book that he is far ahead of his time.He has written the kind ofbook, a "gold standard" if you will, upon which all other textsin the field shall be judged.If I were taking a class which covered thesubject of bioinformatics, I would definitely want this to be my resourcefor information.Clear, concise and unpretentious, Rashidi lays everythingout vividly so that anyone from the undergraduate to the post-graduatestudent may marvel at the wonders of bioinformatics.My only complaint isthat I think it should have been titled "The Bible ofBioinformatics" because its wealth of information is so epic andcomplete.There is no need to look for another book.Rashidi's has itall! ... Read more

Product Description
Bioinformatics is contributing to some of the most important advances in medicine and biology. At the forefront of this exciting new subject are techniques known as artificial intelligence which are inspired by the way in which nature solves the problems it faces. This book provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up ‘intelligent bioinformatics’.

Intelligent Bioinformatics requires only rudimentary knowledge of biology, bioinformatics or computer science and is aimed at interested readers regardless of discipline. Three introductory chapters on biology, bioinformatics and the complexities of search and optimisation equip the reader with the necessary knowledge to proceed through the remaining eight chapters, each of which is dedicated to an intelligent technique in bioinformatics. 

The book also contains many links to software and information available on the internet, in academic journals and beyond, making it an indispensable reference for the 'intelligent bioinformatician'.

Intelligent Bioinformatics will appeal to all postgraduate students and researchers in bioinformatics and genomics as well as to computer scientists interested in these disciplines, and all natural scientists with large data sets to analyse.

... Read more

Product Description
DNA microarrays have revolutionized molecular biology and are becoming a standard tool in the field. Dov Stekel's book is a comprehensive guide to the mathematics, statistics and computing required to use microarrays successfully. Unlike traditional molecular biology, the successful use of DNA microarrays requires the application of statistics and computing to design the arrays and experiments, and to analyze and manage the data. This book is written for researchers, clinicians and laboratory managers. ... Read more

Customer Reviews (8)

Very good introduction to microarray bioinformatics
This is a very clearly written and easy to read introduction to microarray bioinformatics. It builds a basic basis of knowledge in a very short time, so it is a great start for beginners in the field. By the end of the book you also have a pretty clear sense of what you might want to read in more depth. It does not treat any of the subjects in great detail, but does have reading suggestions for each chapter, including books and original papers.Also, the bioinformatics concepts are explained in a very logical and easy to grasp manner, so the biologist or physician with no computational background will find it particularly useful.

Mildly disappointing
I'm not a biologist but became curious about the microarray technology. Although the book seems to cover the important aspects (as far as I can tell from browsing), it managed to annoy me. The author did not make effort to provide something very basic like a clear vocabulary.

Example: he starts using "spot" and "feature" without making effort to explain what they mean in the context of microarrays. At times it seems he treats them as synonyms which is confusing. I consulted the index hoping to find somewhere precise definition of these terms but to no avail. At the end, I had to go to Wikipedia and various other pages which did the job but then if you have to use internet to understand the book than why not just get everything from the web and save the money for the book?

Noting that the target audience are novices in the area of microarrays (experts won't find anything valuable here), the book does a poor job of serving them. To recap: "Nice try. Could do better"

Great Introduction to Microarray Analysis
This is an excellent introduction to microarray analysis. It is great at explaining the theory behind normalization, clustering, and dimensionality reduction without getting hung up on the statistics behind it. If you are looking for an exhaustive statistical treatment on the topic, this is not the book. But it will give you excellent background on these techniques that make reading statistical papers on the topic much easier for the non-statistics biologist.

Highly recommended.

Neat little book on microarrays
Without question this short paperback is a nifty little text. What it does is provide the beginner with a basic brief overview in covering all major aspects of microarrays.

What you have to keep in mind is this book is intended for those who want a brief overview of all aspects of microarrays. Its a "forest for the trees" book on microarrays. The writing is very good and easy to follow, and its a great introductory text and reasonably priced.

Regardless of ones formal training, (e.g. Biology, Statistics, Computer Science, ... , health science) I think it would make an excellent little basic reference on ones bookshelf or to just have around in the lab for undergraduates/beginning graduate students.

Bottomline: If you prefer to learn things by starting at the start and not at the end then consider this book; Indeed its a great starter book to get your feet a little wet before jumping in over your head to the more gnarly stuff.

If you are new to microarray, get this book.
This book describes basic concepts and procedures for those who are new to microarray. I'd recommend that a reader should use this book to grasp what microarray is. You won't be able to know anything in depth from this book but it will be nice to have this if you have trouble in understanding a more challenging book. Once you read this book, please go ahead and read another book since this book doesn't tell you everything about microarray. It's just a basic overview... i was glad that I used this book as my first microarray textbook.... ... 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 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
Provides a broad, application-oriented overview of this technology. The state-of-the-art in bioinformatics is evaluated equally from a global view by introducing real application scenarios. ... Read more

Product Description
The rapidly evolving field of protein science has now come to realize the ubiquity and importance of protein-protein interactions. It had been known for some time that proteins may interact with each other to form functional complexes, but it was thought to be the property of only a handful of key proteins. However, with the advent of high throughput proteomics to monitor protein-protein interactions at an organism level, we can now safely state that protein-protein interactions are the norm and not the exception. Thus, protein function must be understood in the larger context of the various binding complexes that each protein may form with interacting partners at a given time in the life cycle of a cell. Proteins are now seen as forming sophisticated interaction networks subject to remarkable regulation. The study of these interaction networks and regulatory mechanism, which I would like to term "systems proteomics," is one of the thriving fields of proteomics. The bird-eye view that systems proteomics offers should not however mask the fact that proteins are each characterized by a unique set of physical and chemical properties. In other words, no protein looks and behaves like another. This complicates enormously the design of high-throughput proteomics methods. Unlike genes, which, by and large, display similar physico-chemical behaviors and thus can be easily used in a high throughput mode, proteins are not easily amenable to the same treatment. It is thus important to remind researchers active in the proteomics field the fundamental basis of protein chemistry. This book attempts to bridge the two extreme ends of protein science: on one end, systems proteomics, which describes, at a system level, the intricate connection network that proteins form in a cell, and on the other end, protein chemistry and biophysics, which describe the molecular properties of individual proteins and the structural and thermodynamic basis of their interactions within the network. Bridging the two ends of the spectrum is bioinformatics and computational chemistry. Large data sets created by systems proteomics need to be mined for meaningful information, methods need to be designed and implemented to improve experimental designs, extract signal over noise, and reject artifacts, and predictive methods need to be worked out and put to the test. Computational chemistry faces similar challenges. The prediction of binding thermodynamics of protein-protein interaction is still in its infancy. Proteins are large objects, and simplifying assumptions and shortcuts still need to be applied to make simulations manageable, and this despite exponential progress in computer technology. Finally, the study of proteins impacts directly on human health. It is an obvious statement to say that, for decades, enzymes, receptors, and key regulator proteins have been targeted for drug discovery. However, a recent and exciting development is the exploitation of our knowledge of protein-protein interaction for the design of new pharmaceuticals. This presents particular challenges because protein-protein interfaces are generally shallow and interactions are weak. However, progress is clearly being made and the book seeks to provide examples of successes in this area. ... Read more

Product Description

This book constitutes the thoroughly refereed post-proceedings of the First VLDB 2006 International Workshop on Data Mining and Bioinformatics, VDMB 2006, held in Seoul, Korea in September 2006 in conjunction with VLDB 2006.

The 15 revised full papers presented together with an invited talk were carefully reviewed and selected from 30 submissions. The papers cover various topics in the areas of microarray data analysis, bioinformatics system and text retrieval, application of gene expression data, and sequence analysis.

Product Description
Univ. College, Cork, Ireland. Thorough and authoritative account of current techniques and approaches in the field. Covers searching information on entire protein families as well as searching with single sequences. Also describes methods for computer networking for the molecular biologist. Softcover, hardcover also available. ... Read more

Customer Reviews (2)

Great book for protein lovers!
The title of this collection of texts is slightly misleading because the book is entirely devoted to proteins. It does not cover either DNA sequence analysis or nucleic acid structure prediction. Nor does it expose methods of "genome informatics" such as computer-assisted genome annotation or function-associated genome segmenting. Moreover the problematics of molecular evolution is covered only as much as protein phylogeny and homology is discussed. There is virtually no mention of methods for studying genome evolution.

Despite the above negatives the book provides a remarkable survey and tutorial of protein sequence and structure analysis. The editors introduction (Higgins and Taylor) is brief, precise and to the point. Chapter 1 (Jones and Hadley) and Chapter 2 (Johnson and Lehtonen) constitute a tutorial of protein structure analysis. Both chapters are likely to be informative for the beginners and enjoyable by the experts. Chapter 6 (Heringa) and Chapter 8 (Yona and Brenner) are real masterpieces and should be read by all practitioners of bioinformatics as well as by all individuals who want to learn methods of sequence analysis. These two chapters and the editor's introduction make the entire book a valuable desk reference for practitioners and a candidate textbook for students. Just to be completely fair I need to say that Chapter 5 (Henikoff and Henikoff) is potentially confusing and poorly written. The same - although to a lesser degree - applies to Chapter 9 (Harper.)

In summary: Higgins and Taylor have assembled a superb collection of short texts in protein sequence and structure analysis. Practitioners of both bioinformatics and protein biochemistry should use this book as a desk reference. Those who want to learn about bioinformatics will certainly benefit from reading selected chapters of this book as well. The book would not be harmed if it failed to contain confusing and poorly written Chapter 5 (Henikoff and Henikoff) and Chapter 9 (Harper.)

A great blend of biology and computer science
Gives a great overview of bioinformatic techniques in "sequence analysis and searching" and "protein structure analysis and prediction." Then it gives an overview of gene databases online as do all other bioinformatics books. The best part about it is that it spends 70% talking about new biology techniques which greatly helps a computer scientist like me to get into the field. Recommended. ... Read more

Product Description
Provides an overview of the rapidly evolving field of genomics with coverage of nucleic acid technologies, proteomics and bioinformatics. It includes chapters on applications in human health, agriculture and comparative genomics and also contains two chapters on the legal and ethical issues of genomics, a topic that is becoming increasingly important as genomics moves out of the laboratory into practical applications. ... Read more

Product Description
Bioinformatics brings computational methods to the analysis andprocessing of genomic data. Bioinformatics: Databases andSystems focuses on the issues of system building and data curationthat dominate the day-to-day concerns of bioinformatics practitioners.Included are chapters by many of today's leading bioinformaticspractitioners, describing most of the current paradigms of systembuilding and curation, including both their strengths and weaknesses.Biological topics covered include sequence databases, metabolicpathways, phenotypes, variety collections, gene expression atlases andneuroinformatics. Species range from bacteria to mammals to plants.Software systems and technologies covered include OPM, CORBA, SRS,KLEISLI, ACEDB, Web-based integration and laboratory workflow. Bioinformatics: Databases and Systems provides a valuableintroduction for newcomers to the field, and a useful reference forveterans. ... Read more

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GET FULLY UP-TO-DATE ON BIOINFORMATICS-THE TECHNOLOGY OF THE 21ST CENTURY

Bioinformatics showcases the latest developments in the field along with all the foundational information you'll need. It provides in-depth coverage of a wide range of autoimmune disorders and detailed analyses of suffix trees, plus late-breaking advances regarding biochips and genomes.

Featuring helpful gene-finding algorithms, Bioinformatics offers key information on sequence alignment, HMMs, HMM applications, protein secondary structure, microarray techniques, and drug discovery and development. Helpful diagrams accompany mathematical equations throughout, and exercises appear at the end of each chapter to facilitate self-evaluation.

This thorough, up-to-date resource features:

• Worked-out problems illustrating concepts and models
• End-of-chapter exercises for self-evaluation
• Material based on student feedback
• Illustrations that clarify difficult math problems
• A list of bioinformatics-related websites

Bioinformatics covers:

• Sequence representation and alignment
• Hidden Markov models
• Applications of HMMs
• Gene finding
• Protein secondary structure prediction
• Microarray techniques
• Drug discovery and development
• Internet resources and public domain databases

Product Description
Bioinformatics, Biocomputing and Perl presents a modern introduction to bioinformatics computing skills and practice. Structuring its presentation around four main areas of study, this book covers the skills vital to the day-to-day activities of today’s bioinformatician. Each chapter contains a series of maxims designed to highlight key points and there are exercises to supplement and cement the introduced material. 

Working with Perl presents an extended tutorial introduction to programming through Perl, the premier programming technology of the bioinformatics community. Even though no previous programming experience is assumed, completing the tutorial equips the reader with the ability to produce powerful custom programs with ease.

Working with Data applies the programming skills acquired to processing a variety of bioinformatics data. In addition to advice on working with important data stores such as the Protein DataBank, SWISS-PROT, EMBL and the GenBank, considerable discussion is devoted to using bioinformatics data to populate relational database systems.  The popular MySQL database is used in all examples.

Working with the Web presents a discussion of the Web-based technologies that allow the bioinformatics researcher to publish both data and applications on the Internet.

Working with Applications shifts gear from creating custom programs to using them. The tools described include Clustal-W, EMBOSS, STRIDE, BLAST and Xmgrace. An introduction to the important Bioperl Project concludes this chapter and rounds off the book.

... Read more

Customer Reviews (2)

Bioinformatics Biocomputing and Perl is a reasonable tutorial to Perl.
I like this book as a tutorial. I am teaching myself Perl with this book. The chapter examples are good practice and the exercises at the end of the chapters are reasonable. I am about 1/4 through the book, and so far am enjoying the learning process.

Worst bioinformatics book I have read
I have been programming and working as a biologist for the past 6 years, but I have had only a small exposure to Perl.When I read this book description, I was excited since it indicated that Perl would be taught from the ground up and from the bioinformatics perspective.While the perspective is as advertised, this is still a terrible book.Unless you know something about Perl (and programming in general) before you begin, you will be lost.The authors organize some material well, but often relevant items are completely missing.They almost completely abandon Windows users when it would only take a few more sentences to address the difference between Unix and Windows.The end of chapter exercises are poorly thought out and do not provide sufficient practice for the novice.Frequently I found myself referring to "Beginning Perl for Bioinformatics" to make sense of the Moorhouse and Barry book. ... Read more

Product Description
Aimed at students of biotechnology, this work describes the methods used to store, receive, and derive data from databases using various tools. ... Read more

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Bioinformatics is growing by leaps and bounds; theories/algorithms/statistical techniques are constantly evolving. Nevertheless, a core body of algorithmic ideas have emerged and researchers are beginning to adopt a "problem solving" approach to bioinformatics, wherein they use solutions to well-abstracted problems as building blocks to solve larger scope problems.

The Problem Solving Handbook for Computational Biology and Bioinformatics is an edited volume contributed by world renowned leaders in this field. This comprehensive handbook with problem solving emphasis, covers all relevant areas of computational biology and bioinformatics. Web resources and related themes are highlighted at every opportunity in this central easy-to-read reference.

Designed for advanced-level students, researchers and professors in computer science and bioengineering as a reference or secondary text, this handbook is also suitable for professionals working in this industry.

... Read more

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

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.

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