Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology 1st Edition by Dan Gusfield (PDF)

Description

Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today’s applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics.

User’s Reviews

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 This book describes a range of string problems in computer science and molecular biology and the algorithms developed to solve them.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐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. For that, Durbin, Eddy, Krogh and Mitchison’s “Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acides” is a good choice, or for those more interested in language than biology, Manning and Schuetze’s “Statistical Natural Language Processing”. There is also no information on more structured string matching models such as context-free grammars, as are commonly used to analyze RNA folding or natural language syntax. Luckily, Durbin et al. and Manning and Schuetze also provide excellent coverage of these higher-order models in their books.This book is not about efficient implementation. If you need to build these algorithms, you’ll also need to know how to write efficient code and tune it for your needs. This is an algorithms book, pure and simple.As a computer scientist, I found the discussions of computational biology to be more enlightening than in other textbooks on similar topics such as Durbin et al., because Gusfield does not assume the reader has any background in cellular biology. Instead, he provides his own clear and gentle introductions illustrated with algorithms, applications, open problems and extensive references. Like most Cambridge University Press books, this one is beautifully typeset and edited.

⭐Great explanations on algorithms, with rigorous enough proofs and reasoning for a complete theoretic understanding.Although it says algorithms on strings, trees and sequences, the only tree algorithms are the ones that has to do with string, which is the main theme for the book. Meaning, there isn’t anything about trees that don’t have to do with strings, like binary search trees for example.Even if you don’t do computational biology, if you’re learning string algorithms, then I definitely recommend this book.

⭐very good

⭐Product as expected

⭐The book is very accessible for clearly and concisely describing the challenging algorithms it presents. It is a great tool for learning the algorithms necessary for effective software design in bioinformatics.

⭐great knowledge base for developer in data science

⭐Without doubt this book is the best book about string algorithms, and sometime far beyond that. It will definitely change the way of your thinking.

⭐top quality product, good price and recommended

⭐Still the best explanation of suffix trees and their applications you can find in a textbook. This book would be perfect for a second course on algorithmics. The reader is expected to master the basics, so make sure you know about standard data structures and algorithmics first (dynamic programming, priority heaps, hashing, divide-and-conquer, that kind of stuff), and then get this book.Hopefully, a second edition will cover recent advances in string algorithms, particularly suffix arrays.

⭐Ich habe mir dieses Buch gekauft um mich in den Themenkomplex ein zu Arbeiten, und ich muss sagen das es dafür bisjetzt Ideal war. Es eignet sich aber auch gut als Nachschlagewerk, wobei ich gestehen muss das ich noch keinen Blick in andere Algorithmenbücher geworfen habe.Negativ aufgefallen ist mir das Kapitel über “Lowest Common Ancestor Retrieval”, er führt zwar die Idee des Algorithmus ausführlich aus dennoch ist die Idee unnötig kompliziert und jedem sei das Paper “The LCA Problem Revisited” von Michael A. Bender und Martín Farach-Colton entfohlen die eine genauso schnelle, aber einfachere Methode haben.J’ai reçu le livre très rapidement, il était super bien emballe et en parfait état pour un super prix. Super vendeur! Je recommande.This is the bible of String algorithms!

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