Computational Molecular Biology: An Introduction

hunucce

Computational Molecular Biology: An Introduction
By Peter Clote, Rolf Backofen,


Publisher:  Wiley
Number Of Pages:  286
Publication Date:  2000-09-15
Sales Rank:  3526330
ISBN / ASIN:  0471872512
EAN:  9780471872511
Binding:  Hardcover
Manufacturer:  Wiley
Studio:  Wiley
Average Rating:  2.5
Total Reviews:  3

http://rapidshare.com/files/12766717/0471872512.rar
OR
http://mihd.net/dkw9t3

--------------------------------------------------------------------------------

Book Description: )

Recently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and archiving. This requirement has given birth to the truly interdisciplinary field of computational biology, or bioinformatics, a subject reliant on both theoretical and practical contributions from statistics, mathematics, computer science and biology.

* Provides the background mathematics required to understand why certain algorithms work
* Guides the reader through probability theory, entropy and combinatorial optimization
* In-depth coverage of molecular biology and protein structure prediction
* Includes several less familiar algorithms such as DNA segmentation, quartet puzzling and DNA strand separation prediction
* Includes class tested exercises useful for self-study
* Source code of programs available on a Web site

Primarily aimed at advanced undergraduate and graduate students from bioinformatics, computer science, statistics, mathematics and the biological sciences, this text will also interest researchers from these fields.





--------------------------------------------------------------------------------

Date: 2004-02-12  Rating: 2
Review:
Don't start with this book

In general I agree with the two previous reviews.

This book is not very good as an introduction. First read some other book such as Setubal and Meidanis, \"Introduction to Computational Molecular Biology\"; or Krane & Raymer, \"Fundamental Concepts of Bioinformatics\". These books have more readable narrative and examples.

The writing in this book is obtuse. It is written like an advanced abstract math book, not like an ostensibly applied science book. The notation is unnecessarily intricate. Even though it says \"Introduction\" in the title, there are very few tutorial examples. This is just for mathematicians/computer scientists: no biologist I have ever known would/could read this and really understand the algorithms.

This book does, however, have one of the more complete detailed descriptions of various algorithms used for sequence matching, etc. If you have read some other books and are looking for more details on algorithms, then this is your book. But I'm still waiting for THE ultimate Computational Biology book!



Date: 2001-03-20  Rating: 2
Review:
Unsuitable for its stated purpose.

The book purports to be a \"self-contained introduction\" to computational biology. It fails on both counts due to its excessive ambition, its opaque pedagogy, and a large number of significant typographical errors, such as entire subroutines missing from pseudocode examples. Undergraduates seeking an accessible survey are advised to look elsewhere.

That said, the mathematical rigor of the text makes it ideal for students who have moved beyond the need for accessible surveys and wish to improve their fundamental understanding of the field.



Date: 2000-11-22  Rating: 3
Review:
Interesting but not very good for beginners

This is an unusual book. The authors obviously have not been aquinted with biomolecular sequence analysis and fail to give state-of-the-art references to research work in this field. The same comment applies to the description of applications of Shannon communication theory to DNA and protein sequence analysis. The enormous impact of these applications in the 1970s, 1980s and 1990s is not reflected in the book and one could wonder why the authors bother to write of Shannon theory at all. In addition to the above misgivings the authors decided to confuse the reader by including a discussion of quite controversial relationship between Shannon entropy and thermodynamic entropy. Both computational and laboratory biologists will not benefit from this kind of confusion. Mathematicians and computer scientist will probably be mislead by a superficial treatment of this quite intricate topic. Physicists and chemist will probably be able to sort out useful information from over-interpretations but they may wonder why this issue is discussed in a computational biology text.

Despite the above critique I like the book. Organization of this text is interesting and distinctly different form other books in the field. Chapters on sequence alignment and phylogenetic trees are most interesting and original. They should probably be read in conjunction with more systematic textbooks such as Gusfield's \"Algorithms on strings, trees and sequences\" or Li's \"Molecular evolution.\" Despite many misgivings (see the beginning paragraph of this review) the mathematical primer (chapter 2) is very much worth reading for its originality and compactness. Particularly sections about probability distributions and combinatorial optimization can be useful for non-mathematicians and interesting for those who are mathematically literate. However, care should be exercised (see the beginning paragraph) while reading sections about entropy and about optimality of the genetic code. Chapter 1 about principles of molecular biology is not very good for non-biologists because it is too compact. Chapter about structure prediction is also too compact to be either understandable to non-specialists or enjoyable by the experts. If the authors' ambitious approach was to be sustained, this chapter should probably be expanded to the size of entire book. Exercises at the end of every chapter of the book are interesting and worth the reader's attention. It would probably be good to have access to solutions of all exercises but it is a minor problem.

In summary: it is an interesting book but it should be read in conjunction with other texts. It should not be recommended to the beginners in computational biology. Mathematically seasoned readers will enjoy reading selected parts of this book. It would be nice if the publisher could consider lowering price of this book (already in paperback.)