遺伝情報は、核酸、あるいはアミノ酸をアルファベットとみなす文字列とみなすことができる。
ヒトゲノム計画によりゲノムシーケンスがほぼ解明されてきており、この大量の文字列を解析するのに様々な文字列マッチングが有用である。
とりわけ本書で詳説されるSuffix Treeは、部分文字列を非常に効率よく同定できるため、応用も多い。
これはゲノムだけでなくウェブ上や辞書のテキストも文字列であるため、検索語を非常に効率よく検索できることを意味する。
とりわけ、ゲノム情報での使い方がくわしいため、バイオインフォマティクスをやっている方、やろうと思われる方は、読んでおくことをお奨めします。
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発送元: SuperBookDeals_ 販売者: SuperBookDeals_
¥15,862¥15,862 税込
ポイント: 159pt
(1%)
配送料 ¥257 6月29日-7月10日にお届け
発送元: SuperBookDeals_
販売者: SuperBookDeals_
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Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology ハードカバー – 1997/1/15
英語版
Dan Gusfield
(著)
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購入オプションとあわせ買い
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 (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises 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. Its discussion of current algorithms and techniques also makes it a reference for professionals.
- 本の長さ556ページ
- 言語英語
- 出版社Cambridge University Press
- 発売日1997/1/15
- 寸法18.42 x 3.81 x 27.31 cm
- ISBN-100521585198
- ISBN-13978-0521585194
商品の説明
レビュー
'The readers of this book will be serious programmers, but of course anybody working in bio-computing will find the book of immense practical, scientific and commercial importance … you should get the book, whether you want to do some string processing, fundamental computing research, or want to impress a biotech firm.' Harold Thimbleby, The Times Higher Education Supplement
'… could well be used as the basis for a graduate-level course, particularly as it contains over 400 exercises to reinforce presented material and to develop further topics. It is recommended most highly.' P. Gibbons, Zentralblatt für Mathematik
'… could well be used as the basis for a graduate-level course, particularly as it contains over 400 exercises to reinforce presented material and to develop further topics. It is recommended most highly.' P. Gibbons, Zentralblatt für Mathematik
登録情報
- 出版社 : Cambridge University Press (1997/1/15)
- 発売日 : 1997/1/15
- 言語 : 英語
- ハードカバー : 556ページ
- ISBN-10 : 0521585198
- ISBN-13 : 978-0521585194
- 寸法 : 18.42 x 3.81 x 27.31 cm
- Amazon 売れ筋ランキング: - 232,676位洋書 (洋書の売れ筋ランキングを見る)
- - 6位Bioinformatics (洋書)
- - 174位Pattern Recognition Algorithms
- - 874位Evolution (洋書)
- カスタマーレビュー:
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他の国からのトップレビュー
Fred Janon
5つ星のうち5.0
Excellent vendeur
2021年3月25日にフランスでレビュー済みAmazonで購入
J'ai reçu le livre très rapidement, il était super bien emballe et en parfait état pour un super prix. Super vendeur! Je recommande.
Kedar Mhaswade
5つ星のうち5.0
Five Stars
2017年7月14日にインドでレビュー済みAmazonで購入
This is the bible of String algorithms!
Public Name
5つ星のうち5.0
Get your fix of suffix trees here
2015年8月3日にカナダでレビュー済みAmazonで購入
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.
Hopefully, a second edition will cover recent advances in string algorithms, particularly suffix arrays.
Mr. S. Fernea
5つ星のうち5.0
good price and recommended
2015年3月18日に英国でレビュー済みAmazonで購入
top quality product, good price and recommended
Bob Carpenter
5つ星のうち5.0
Definitive String Algorithms Text
2003年1月4日にアメリカ合衆国でレビュー済みAmazonで購入
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.
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.