Algorithms on Strings, Trees, and Sequences

Algorithms on Strings, Trees, and Sequences PDF

Author: Dan Gusfield

Publisher: Cambridge University Press

Published: 1997-05-28

Total Pages: 556

ISBN-13: 1139811002

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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.

Algorithms on Strings, Trees, and Sequences

Algorithms on Strings, Trees, and Sequences PDF

Author: Dan Gusfield

Publisher: Cambridge University Press

Published: 1997-05-28

Total Pages: 556

ISBN-13: 0521585198

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

Algorithms on Strings

Algorithms on Strings PDF

Author: Maxime Crochemore

Publisher: Cambridge University Press

Published: 2007-04-09

Total Pages: 392

ISBN-13: 1139463853

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The book is intended for lectures on string processes and pattern matching in Master's courses of computer science and software engineering curricula. The details of algorithms are given with correctness proofs and complexity analysis, which make them ready to implement. Algorithms are described in a C-like language. The book is also a reference for students in computational linguistics or computational biology. It presents examples of questions related to the automatic processing of natural language, to the analysis of molecular sequences, and to the management of textual databases.

Biological Sequence Analysis

Biological Sequence Analysis PDF

Author: Richard Durbin

Publisher: Cambridge University Press

Published: 1998-04-23

Total Pages: 372

ISBN-13: 113945739X

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Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

An Introduction to Bioinformatics Algorithms

An Introduction to Bioinformatics Algorithms PDF

Author: Neil C. Jones

Publisher: MIT Press

Published: 2004-08-06

Total Pages: 460

ISBN-13: 9780262101066

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An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.

Text Algorithms

Text Algorithms PDF

Author: Maxime Crochemore

Publisher: Maxime Crochemore

Published: 1994

Total Pages: 396

ISBN-13: 0195086090

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This much-needed book on the design of algorithms and data structures for text processing emphasizes both theoretical foundations and practical applications. It is intended to serve both as a textbook for courses on algorithm design, especially those related to text processing, and as a reference for computer science professionals. The work takes a unique approach, one that goes more deeply into its topic than other more general books. It contains both classical algorithms and recent results of research on the subject. The book is the first text to contain a collection of a wide range of text algorithms, many of them quite new and appearing here for the first time. Other algorithms, while known by reputation, have never been published in the journal literature. Two such important algorithms are those of Karp, Miller and Rosenberg, and that of Weiner. Here they are presented together for the fist time. The core of the book is the material on suffix trees and subword graphs, applications of these data structures, new approaches to time-space optimal string-matching, and text compression. Also covered are basic parallel algorithms for text problems. Applications of all these algorithms are given for problems involving data retrieval systems, treatment of natural languages, investigation of genomes, data compression software, and text processing tools. From the theoretical point of view. the book is a goldmine of paradigms for the development of efficient algorithms, providing the necessary foundation to creating practical software dealing with sequences. A crucial point in the authors' approach is the development of a methodology for presenting text algorithms so they can be fully understood. Throughout, the book emphasizes the efficiency of algorithms, holding that the essence of their usefulness depends on it. This is especially important since the algorithms described here will find application in "Big Science" areas like molecular sequence analysis where the explosive growth of data has caused problems for the current generation of software. Finally, with its development of theoretical background, the book can be considered as a mathematical foundation for the analysis and production of text processing algorithms.

Proceedings of International Joint Conference on Computational Intelligence

Proceedings of International Joint Conference on Computational Intelligence PDF

Author: Mohammad Shorif Uddin

Publisher: Springer

Published: 2019-07-03

Total Pages: 749

ISBN-13: 981137564X

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This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14–15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

Average Case Analysis of Algorithms on Sequences

Average Case Analysis of Algorithms on Sequences PDF

Author: Wojciech Szpankowski

Publisher: John Wiley & Sons

Published: 2011-10-14

Total Pages: 580

ISBN-13: 1118031024

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A timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume. * Tools are illustrated through problems on words with applications to molecular biology, data compression, security, and pattern matching. * Includes chapters on algorithms and data structures on words, probabilistic and analytical models, inclusion-exclusion principles, first and second moment methods, subadditive ergodic theorem and large deviations, elements of information theory, generating functions, complex asymptotic methods, Mellin transform and its applications, and analytic poissonization and depoissonization. * Written by an established researcher with a strong international reputation in the field.