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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology 1st Edition

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ISBN-13: 978-0521585194
ISBN-10: 0521585198
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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology + Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids + An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)
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Editorial Reviews

Review

"...an important summary of the state of the art in pattern matching and an indicator of the importance biological problems have assumed among many researchers. It will hopefully encourage them to question the importance of the problems they endeavor to solve." SIGACT News

"The book will be profitable both for graduate students in computer science and for biologists with a good background in programming." Mathematical Reviews

"One often encounters in this book thought-provoking quotes relating to the importance of sequence analysis...Also found in the text are interesting biological examples of sequence analysis..." Cell

Book Description

String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data produced by various genome projects. This book explains a wide range of computer methods for string processing. It also contains extensive discussions on biological problems that are cast as string problems, and on techniques to solve them. The book is both a reference for computer scientists and computer-oriented professionals in biology and bio-informatics and a textbook for graduate and advanced undergraduate courses on string algorithms and on computational biology.
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Product Details

  • Hardcover: 556 pages
  • Publisher: Cambridge University Press; 1 edition (May 28, 1997)
  • Language: English
  • ISBN-10: 0521585198
  • ISBN-13: 978-0521585194
  • Product Dimensions: 7 x 1.2 x 10 inches
  • Shipping Weight: 3.4 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (13 customer reviews)
  • Amazon Best Sellers Rank: #412,844 in Books (See Top 100 in Books)

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65 of 67 people found the following review helpful By Dr. Lee D. Carlson HALL OF FAMEVINE VOICE on April 4, 2001
Format: Hardcover
This textbook gives a rigorous introduction to the algorithms of computational biology from the standpoint of theoretical computer science. It does however give the reader an overview of the practical application of these algorithms to the subject. The author gives a very detailed discussion of the most important results in the field, but the book is very dense: there are 228 definitions, 127 theorems, 490 references, and over 400 exercises that both illustrate the topics in the book and extend them. The author omits any real source code, but does give a URL where code for many of the algorithms can be found.
The author restricts his attention to deterministic approaches to string matching and comparison, and thus there is no treatment of hidden Markov models or Monte Carlo methods. The major algorithms such as the Aho-Corasick, Boyer-Moore, Knuth-Morris-Pratt, Needleman-Winsch, and Smith-Waterman are discussed and brilliantly motivated in the book. The author employs very effective diagrams to illustrate the matching concepts that are detailed in the book.
The book does require some time to read but it is worth the effort. Also, the exercises can be challenging but some should he done in order to understand the concepts in the book. The empirical results of the algorithms as sequence databases are also included, with FASTA, BLAST, BLOCKS, BLOSUM, and PROSITE are discussed in detail. The chapter that discusses these is the least mathematical of all the ones in the book and was no doubt included to connect the reader with real-world applications of the techniques in the book.
The last quarter of the book is a lot more trendy than the rest, with emphasis placed on algorithms for physical mapping, fragment assembly, and phylogenetic trees.
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38 of 38 people found the following review helpful By Bob Carpenter on January 4, 2003
Format: Hardcover Verified Purchase
If you like definition-theorem-proof-example and exercise books, Gusfield's book is the definitive text for string algorithms. The algorithms are abstracted from their biological applications, and the book would make sense without reading a single page of the biological motivations. Gusfield aims his book at readers who are fluent in basic algorithms and data structures (at the level of Cormen, Leisersohn and Rivest's excellent text). The exercises are wonderfully illustrative, being neither trivial nor impossible.
All of the major exact string algorithms are covered, including Knuth-Morris-Pratt, Boyer-Moore, Aho-Corasick and the focus of the book, suffix trees for the much harder probem of finding all repeated substrings of a given string in linear time. In addition to exact string matching, there are extensive discussions of inexact matching. Even the discussions of widely known topics like dynamic programming for edit distance are insightful; for instance, we find how to easily cut space requirements from quadratic to linear. There is also a short chapter on semi-numerical matching methods, which are also of use in information retrieval applications. Inexact matching is extended to the threshold all-against-all problem, which finds all substrings of a string that match up to a given edit distance threshold. The theoretical development concludes with the much more difficult problem of aligning multiple sequences with ultrametric trees, with applications to phylogenetic alignment for evolutionary trees (an approach that has also been applied to the evolution of natural languages).
Note that there is no discussion of statistical string matching.
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31 of 31 people found the following review helpful By A Customer on June 11, 1998
Format: Hardcover
This is THE book on string algorithms; covers all the normal exact match algs (Z, BM, KMP) and then goes on to discuss suffix trees in great depth (but with great clarity!). The second half of the book deals with inexact matching mostly using dynamic-programming-based algs. Some of the stuff generalizes nicely to non-string DP algs as well. Worth the investment just for increasing "algorithmic maturity", not to mention Gusfield's gift for clear exposition makes it a pleasant read.
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24 of 25 people found the following review helpful By Peter Friend on June 15, 1998
Format: Hardcover
When you try to teach yourself a subject, you end up buying large numbers of books so that all of the little gaps are filled. Unfortunately, I didn't find this book until AFTER I spent a fortune on others. Don't be thrown by the "biology" in the title. This book clearly explains the numerous algorithms available for string searching and matching. And it does so without burying you in theory or pages full of math. By far, the best book on the subject I have found, especially if you are "into" genetics or are trying to learn about these algorithms on your own.
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17 of 17 people found the following review helpful By Shlomo Yona on November 5, 2001
Format: Hardcover
Excellent book on String Algorithms. A lot of material. This is not an easy read, though, relatively not difficult for an algorithms and data-structures book.
This is the most complete resource i could find about suffix trees, how to implement them, usages, and algorithms. Actually, when I took this book, I was interested in suffix arrays. Well - this book explains those better than the original paper do.
Many applications to suffix trees are listed, along with comparisons to other algorithms applied to those problems.
If you need to get into string algorithms from computer science perspective - this is a good book to start. If you want to "feel" of the biologists side of the story, than this is not a good choice.
I use this book as a textbook on the subject, and I'm sure I'll be using it as a reference later on.
This book surely is worth its cost (even if you buy it on Amazon...:-)).
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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology
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