Book Description

* First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches
* Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining
* Discusses principles and classical algorithms on string matching and their role in data mining ... Read more

Reviews (1)

A comprehensive coverage on Data Mining
This book is a distinct addition to the field of data mining in its coverage of topics and ideas.
The good point about this book is that it explains the central concepts in great details with the required rigour and also puts in examples to make them understandable. Its not a typical Theorem , Lemma book , but also do not shy away from the mathematical complexities.
There is adequate coverage of all the standard topics and additionally there are interesting sections on Rough sets and Fuzzy sets, which are generally not available everywhere.
The most important point about this book is that it gives a thorough coverage of Multimedia data and web data and biological data, which is very dificult to get in one place in any book.
A researcher or anyone with adequate background in Mathematics will find this book very helpful in their research.
References are also pretty much exhaustive.
I would have liked to see some more coverage on datawarehouse and complexity analysis of the algorithms mentioned, also some language level implementation examples at least in some appendix to the book. Also a paperback edition is needed as the price is quite high. ... Read more

Book Description

Bioinformatics Software Engineering: Delivering Effective Applications will be useful to anyone who wants to understand how successful software can be developed in a rapidly changing environment.

A handbook, not a textbook, it is not tied to any particular operating system, platform, language, or methodology. Instead it focuses on principles and practices that have been proven in the real world. It is pragmatic, emphasizing the importance of what the author calls Adaptive Programming - doing what works in your situation, and it is concise, covering the whole software development lifecycle in one slim volume.

At each stage, it describes common pitfalls, explains how these can be avoided, and suggests simple techniques which make it easier to deliver better solutions.

"Well thought-out ... addresses many of the key issues facing developers of bioinformatics software."  (Simon Dear, Director, UK Technology and Development, Bioinformatics Engineering and Integration, Genetics Research, GlaxoSmithKline)

Here are some examples from the book itself. 

On software development:

“Writing software properly involves talking to people – often lots of people – and plenty of non-coding work on your part.  It requires the ability to dream up new solutions to problems so complicated that they are hard to describe.”

From description to specification:

“Look for verbs – action words, such as ‘does’, ‘is’ and ‘views’.  Identify nouns – naming words, like ‘user’, ‘home’ and ‘sequence’.  List the adjectives – describing words, for example ‘quick’, ‘simple’ or ‘precise’.

The verbs are the functions that must be provided by your application.  The nouns define the parameters to those functions, and the adjectives specify the constraint conditions under which your program must operate.”

On how to start writing software:

“Handle errors.  Take in data.  Show output.  Get going!”

On testing:

“It may not be physically possible to test every potential combination of situations that could occur as users interact with a program.  But one thing that can be done is to test an application at the agreed extremes of its capability: the maximum number of simultaneous users it has to support, the minimum system configuration it must run on, the lowest communication speed it must cope with, and the most complex operations it must perform.

If your program can cope with conditions at the edge of its performance envelope, it is less likely to encounter difficulties in dealing with less challenging situations.”

On showing early versions of software to users:

“It can be hard explaining the software development process to people who are unfamiliar with it.  Code that to you is nearly finished is simply not working to them, and seeing their dream in bits on the workbench can be disappointing to customers, especially when they were expecting to be able to take it for a test drive.”

On bugs:

“If your users find a genuinely reproducible bug in production code, apologize, fix it fast, and then fix the system that allowed it through.  And tell your customers what you are doing, and why, so they will be confident that it will not happen again.  Everybody makes mistakes.  Don’t make the same ones twice.”

And one last thought on successful software development:

“You have to be a detective, following up clues and examining evidence to discover what has gone wrong and why.  And you have to be a politician, understanding what people want, both in public and in private, and how this is likely to affect what you are trying to do.  This book cannot teach you how to do all of that, but it can help.”

... Read more

Book Description

Bioinformatics of Genome Regulation and Structure covers:

+ regulatory genomic sequences: databases, knowledge bases, computer analysis, modeling, and recognition;+ large-scale genome analysis and functional annotation;+ gene structure detection and prediction;+ comparative and evolutionary genomics;+ computer analysis of genome polymorphism and evolution; computer analysis and modeling of transcription, splicing, and translation; structural computational biology: structure-function organization of genomic DNA, RNA, and proteins;+ gene networks, signal transduction pathways, and genetically controlled metabolic pathways: principles of organization, operation, and evolution;+ data warehousing, knowledge discovery and data mining; and,+ analysis of basic patterns of genome operation, organization, and evolution. The data presented may be used while solving a wide range of problems, both basic and applied, in various directions of molecular biology, molecular genetics, biotechnology, pharmacogenetics, pharmacology, and adjacent fields of medicine, veterinary, and agrobiology. ... Read more

Book Description

Emergent Computation emphasizes the interrelationship of the different classes of languages studied in mathematical linguistics (regular, context-free, context-sensitive, and type 0) with aspects to the biochemistry of DNA, RNA, and proteins. In addition, aspects of sequential machines such as parity checking and semi-groups are extended to the study of the Biochemistry of DNA, RNA, and proteins. Mention is also made of the relationship of algebraic topology, knot theory, complex fields, quaternions, and universal turing machines and the biochemistry of DNA, RNA, and proteins.

Emergent Computation tries to avoid an emphasis upon mathematical abstraction ("elegance") at the expense of ignoring scientific facts known to Biochemists. Emergent Computation is based entirely upon papers published by scientists in well-known and respected professional journals. These papers are based upon current research. A few examples of what is not ignored to gain "elegance":

- DNA exists as triple and quadruple strands

- Watson-Crick complementary bases have mismatches

- There can be more than four bases in DNA

- There are more than sixty-four codons

- There may be more that twenty amino acids in proteins

While Emergent Computation emphasizes bioinformatics applications, the last chapter studies mathematical linguistics applied to areas such as languages found in birds, insects, medical applications, anthropology, etc.

Emergent Computation tries to avoid unnecessary mathematical abstraction while still being rigorous. The demands made upon the knowledge of chemistry or mathematics is minimized as well. The collected technical references are valuable in itself for additional reading.

Book Description

Universite de Geneve, Switzerland. Reviews recent advances in two-dimensional gel electrophoresis, protein microanalysis and bioinformatics. For biologists, clinicians and researchers. 13 international contributors. ... Read more

Reviews (1)

Good Concept Building book.
I bought this book to understand the computer science side of molecular biology. This book gives good treatment of the basics though if you are a programmer and want to get involved straight away, this book will be of little help.

This book helped me understand some concepts, and pointed me to some of the tools and databases that are currently in use in the bioinformatics business. ... Read more

Book Description

This book looks at the mathematical foundations of the models which is crucial for correct interpretation of the outputs of the models. A bioinformatician should be able not only use software packages, but also know the mathematics behind these packages. From this point of view, mathematics departments throughout the world have a major role to play in bioinformatics education by teaching courses on the mathematical foundations of bioinformatics. The author wrote this book based on his lecture notes for his courses. It combines several topics in biological sequence analysis with mathematical and statistical material required for such analysis.

Book Description

This digital document is an article from Biotech Business, published by Worldwide Videotex on September 1, 2000. The length of the article is 653 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

Citation Details
Title: PPGX LAUNCHES GENETRIALS BIOINFORMATICS PLATFORM.
Publication: Biotech Business (Newsletter)
Date: September 1, 2000
Publisher: Worldwide Videotex
Volume: 13Issue: 9Page: NA

Distributed by Thomson Gale ... Read more

Book Description

This digital document is an article from Journal of the American Statistical Association, published by American Statistical Association on June 1, 2003. The length of the article is 1664 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

Citation Details
Title: Statistical Methods in Bioinformatics: An Introduction. (Book Reviews).(Book Review)
Author: Paul Schliekelman
Publication: Journal of the American Statistical Association (Refereed)
Date: June 1, 2003
Publisher: American Statistical Association
Volume: 98Issue: 462Page: 490(2)

Article Type: Book Review

Distributed by Thomson Gale ... Read more

Book Description

This book constitutes the refereed proceedings of the 14th Annual Symposium on Combinatorial Pattern Matching, CPM 2003, held in Morelia, Michoacán, Mexico in June 2003. The 28 revised full papers presented were carefully reviewed and selected from 57 submissions. The papers are devoted to current theoretical and computational aspects of searching and matching strings and more complicate patterns, such as trees, regular expressions, graphs, point sets, and arrays. Among the application fields addressed are computational biology, bioinformatics, genomics, the Web, data compression, coding, multimedia, information retrieval, pattern recognition, and computer vision. ... Read more

Book Description

This book constitutes the refereed proceedings of the 7th International Conference on Parallel Problem Solving from Nature,PPSN 2002, held in Granada, Spain in September 2002.The 90 revised full papers presented were carefully reviewed and selected from 181 submissions. The papers are organized in topical sections on evolutionary algorithms theory, representation and codification, variation operators, evolutionary techniques and coevolution, multiobjective optimization, new techniques for evolutionary algorithms, hybrid algorithms, learning classifier systems, implementation of evolutionary algorithms, applications, and cellular automata and ant colony optimization. ... Read more

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

Book Description

The coupling of biological and electronic systems has in the past few years emerged as a field of increasing importance. Achievements like the cardiac pacemaker have paved the way for more sophisticated approaches, such as the lab-on-a-chip and DNA computers. This book presents reviews on some of the most promising projects in this interdisciplinary research field, covering topics from bioinformatics to biosensor technology. ... Read more

Book 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

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

Book Description

This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Analysis, IDA 2003, held in Berlin, Germany in August 2003. The 56 revised papers presented were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on machine learning, probability and topology, classification and pattern recognition, clustering, applications, modeling, and data processing. ... Read more

Book Description

This book constitutes the thoroughly refereed postproceedings of the International Conference on Computational Methods in Systems Biology, CMSB 2004, held in Paris, France in May 2004.

The 16 revised full papers and 7 revised short papers presented together with an invited paper went through two rounds of reviewing, selection and revision. The papers present a variety of techniques from computer science, such as language design, concurrency theory, software engineering, and formal methods, for biologists, physicists, and mathematicians interested in the systems-level understanding of cellular processes.

Book Description

In this book, leading bioinformatics experts critically review the tools and web servers currently available. Each chapter provides a clear explanation of the use, purpose and future potential of the tools for a given application. Topics covered include the use of multiple alignment methods, analysis of expression data, structural genomics, proteing structure prediction, and much more. An essential book for all scientists working in genomics, proteomics and metabolomics. ... Read more