Algorithms On Strings Trees And Sequences

Author: Dan Gusfield
Editor: Cambridge University Press
ISBN: 9780521585194
Size: 14,32 MB
Format: PDF, Docs
Read: 451

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.

Theoretical Computer Science

Author: Mario Coppo
Editor: Springer Science & Business Media
ISBN: 9783540291060
Size: 15,92 MB
Format: PDF, ePub
Read: 967

This book constitutes the refereed proceedings of the 9th International Conference on Theoretical Computer Science, ICTCS 2005, held at the Certosa di Pontignano, Siena, Italy, in October 2005. The 29 revised full papers presented together with an invited paper and abstracts of 2 invited talks were carefully reviewed and selected from 83 submissions. The papers address all current issues in theoretical computer science and focus especially on analysis and design of algorithms, computability, computational complexity, cryptography, formal languages and automata, foundations of programming languages and program analysis, natural computing paradigms (quantum computing, bioinformatics), program specification and verification, term rewriting, theory of logical design and layout, type theory, security, and symbolic and algebraic computation.

Advances In Mining Graphs Trees And Sequences

Author: Takashi Washio
Editor: IOS Press
ISBN: 9781586035280
Size: 13,83 MB
Format: PDF, ePub, Docs
Read: 636

Ever since the early days of machine learning and data mining, it has been realized that the traditional attribute-value and item-set representations are too limited for many practical applications in domains such as chemistry, biology, network analysis and text mining. This has triggered a lot of research on mining and learning within alternative and more expressive representation formalisms such as computational logic, relational algebra, graphs, trees and sequences. The motivation for using graphs, trees and sequences. Is that they are 1) more expressive than flat representations, and 2) potentially more efficient than multi-relational learning and mining techniques. At the same time, the data structures of graphs, trees and sequences are among the best understood and most widely applied representations within computer science. Thus these representations offer ideal opportunities for developing interesting contributions in data mining and machine learning that are both theoretically well-founded and widely applicable. The goal of this book is to collect recent outstanding studies on mining and learning within graphs, trees and sequences in studies worldwide.


Author: Dan Gusfield
Editor: MIT Press
ISBN: 0262027526
Size: 17,87 MB
Format: PDF, Mobi
Read: 109

Combinatorial structure and algorithms for deducing genetic recombination history, represented by ancestral recombination graphs and other networks, and their role in the emerging field of phylogenetic networks.

Algorithms And Theory Of Computation Handbook Second Edition Volume 1

Author: Mikhail J. Atallah
Editor: CRC Press
ISBN: 9781584888239
Size: 14,78 MB
Format: PDF, Kindle
Read: 294

Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory. This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

String Processing And Information Retrieval

Author: Edleno Moura
Editor: Springer
ISBN: 3319119184
Size: 15,10 MB
Format: PDF, ePub, Docs
Read: 891

This book constitutes the proceedings of the 21st International Symposium on String Processing and Information Retrieval, SPIRE 2014, held in Ouro Preto, Brazil, in October 2014. The 20 full and 6 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers focus not only on fundamental algorithms in string processing and information retrieval, but address also application areas such as computational biology, Web mining and recommender systems. They are organized in topical sections on compression, indexing, genome and related topics, sequences and strings, search, as well as on mining and recommending.

Integer Linear Programming In Computational And Systems Biology

Author: Dan Gusfield
Editor: Cambridge University Press
ISBN: 1108421768
Size: 13,96 MB
Format: PDF, ePub
Read: 325

This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.

Hidden Markov Models For Bioinformatics

Author: T. Koski
Editor: Springer Science & Business Media
ISBN: 9781402001369
Size: 17,92 MB
Format: PDF, ePub, Mobi
Read: 576

The purpose of this book is to give a thorough and systematic introduction to probabilistic modeling in bioinformatics. The book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. Questions of parametric inference, selection between model families, and various architectures are treated. Several examples are given of known architectures (e.g., profile HMM) used in genome analysis. Audience: This book will be of interest to advanced undergraduate and graduate students with a fairly limited background in probability theory, but otherwise well trained in mathematics and already familiar with at least some of the techniques of algorithmic sequence analysis.

Data Mining In Bioinformatics

Author: Jason T. L. Wang
Editor: Springer Science & Business Media
ISBN: 1846280591
Size: 12,82 MB
Format: PDF, Docs
Read: 512

Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Sequence Evolution Function

Author: Eugene Koonin
Editor: Springer Science & Business Media
ISBN: 9781402072741
Size: 13,53 MB
Format: PDF
Read: 254

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.