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

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 Publisher Description (unedited Publisher Data) 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. Library Of Congress Subject Headings For This Publication: Computer Algorithms, Bioinformatics, Molecular Biology Data Processing. Exact Matching: Fundamental Preprocessing And First Algorithms -- Exact Matching: Classical Comparison-based Methods -- Exact Matching: A Deeper Look At Classical Methods -- Seminumerical String Matching -- Introduction To Suffix Trees -- Linear-time Construction Of Suffix Trees -- First Applications Of Suffix Trees -- Constant-time Lowest Common Ancestor Retrieval -- More Applications Of Suffix Trees -- The Importance Of (sub)sequence Comparison In Molecular Biology --core String Edits, Alignments, And Dynamic Programming -- Refining Core String Edits And Alignments -- Extending The Core Problems -- Multiple String Comparison -- The Holy Grail -- Sequence Databases And Their Uses- The Mother Lode -- Maps, Mapping, Sequencing, And Superstrings -- Strings And Evolutionary Trees -- Three Short Topics -- Models Of Genome-level Mutations. Dan Gusfield. Includes Bibliographical References (p. 505-523) And Index. 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 1997 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 2.4.2. Preprocessing for real-time string matching2.5 Exercises; 3 Exact Matching: A Deeper Look at Classical Methods; 3.1 A Boyer-Moore variant with a ""simple"" linear time bound; 3.1.1. Key ideas; 3.1.2. One phase in detail; 3.1.3. Correctness and linear-time analysi; 3.2 Cole's linear worst-case bound for Boyer-Moore; 3.2.1. Cole's proof when the pattern does not occur in the text; 3.2.2. The case when the pattern does occur in the text; 3.2.3. Adding in the bad character rule; 3.3 The original preprocessing for Knuth-Morris-Pratt; 3.3.1. The method does not use fundamental preprocessing 2.1 Introduction2.2 The Boyer-Moore Algorithm; 2.2.1. Right-to-left scan; 2.2.2. Bad character rule; 2.2.3. The (strong) good suffix rule; 2.2.4. Preprocessing for the good suffix rule; 2.2.5. The good suffix rule in the search stage of Boyer-Moore; 2.2.6. The complete Boyer-Moore algorithm; 2.3 The Knuth-Morris-Pratt algorithm; 2.3.1. The Knuth-Morris-Pratt shift idea; The Knuth-Morris-Pratt shift rule; 2.3.2. Preprocessing for Knuth-Morris-Pratt; 2.3.3. A full implementation of Knuth-Morris-Pratt; 2.4 Real-time string matching; 2.4.1. Converting Knuth-Morris-Pratt to a real-time method 3.5.2. Exact matching with wild cards3.5.3. Two-dimensional exact matching; 3.6 Regular expression pattern matching; 3.6.1. Formal definitions; 3.7 Exercises; 4 Seminumerical String Matching; 4.1 Arithmetic versus comparison-based methods; 4.2 The Shift-And method; 4.2.1. How to construct array M; 4.2.2. Shift-And is effective for small patterns; 4.2.3. agrep: The Shift-And method with errors; 4.2.4. How to compute Mk; 4.3 The match-count problem and Fast Fourier Transform; 4.3.1. A fast worst-case method for the match-count problem?; 4.3.2. Using Fast Fourier Transform for match-counts Cover; Half-title; Title; Copyright; Dedication; Contents; Preface; I Exact String Matching: The Fundamental String Problem; 1 Exact Matching: Fundamental Preprocessing and First Algorithms; 1.1 The naive method; 1.1.1. Early ideas for speeding up the naive method; 1.2 The preprocessing approach; 1.3 Fundamental preprocessing of the pattern; 1.4 Fundamental preprocessing in linear time; The Z algorithm; 1.5 The simplest linear-time exact matching algorithm; 1.5.1. Why continue?; 1.6 Exercises; A digression on circular strings in DNA; 2 Exact Matching: Classical Comparison-Based Methods 3.3.2. The easy case3.3.3. The general case; 3.3.4. How to compute the optimized shift values; 3.4 Exact matching with a set of patterns; 3.4.1. Naive use of keyword trees for set matching; 3.4.2. The speedup: generalizing Knuth-Morris-Pratt; 3.4.3. Failure functions for the keyword tree; 3.4.4. The failure links speed up the search; 3.4.5. Linear preprocessing for the failure function; 3.4.6. The full Aho-Corasick algorithm: relaxing the substring assumption; 3.5 Three applications of exact set matching; 3.5.1. Matching against a DNA or protein library of known patterns This volume 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. This 1997 book describes a range of string problems in computer science and molecular biology and the algorithms developed to solve them 4.4 Karp-Rabin fingerprint methods for exact match