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Computer Analysis of Sequence Data, Part I

Author: Annette M. Griffin

Publisher: Springer Science & Business Media

Published: 2008-02-02

Total Pages: 370

ISBN-13: 1592595111

DNA sequencing has become increasingly efficient over the years, resulting in an enormous increase in the amount of data gen- ated. In recent years, the focus of sequencing has shifted, from being the endpoint of a project, to being a starting point. This is especially true for such major initiatives as the human genome project, where vast tracts of DNA of unknown function are sequenced. This sheer volume of available data makes advanced computer methods ess- tial to analysis, and a familiarity with computers and sequence ana- sis software a vital requirement for the researcher involved with DNA sequencing. Even for nonsequencers, a familiarity with sequence analysis software can be important. For instance, gene sequences already present in the databases can be extremely useful in the design of cloning and genetic manipulation experiments. This two-part work on Analysis of Data is designed to be a practical aid to the researcher who uses computers for the acquisition, storage, or analysis of nucleic acid (and/or p- tein) sequences. Each chapter is written such that a competent sci- tist with basic computer literacy can carry out the procedure successfully at the first attempt by simply following the detailed pr- tical instructions that have been described by the author. A Notes section, which is included at the end of each chapter, provides advice on overcoming the common problems and pitfalls sometimes enco- tered by users of the sequence analysis software. Software packages for both the mainframe and personal computers are described.

Computer Analysis of Sequence Data Part II

Author: Annette M. Griffin

Publisher: Springer Science & Business Media

Published: 2008-02-02

Total Pages: 434

ISBN-13: 159259512X

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DNA sequencing has become increasingly efficient over the years, resulting in an enormous increase in the amount of data gener ated. In recent years, the focus of sequencing has shifted, from being the endpoint of a project, to being a starting point. This is especially true for such major initiatives as the human genome project, where vast tracts of DNA of unknown function are sequenced. This sheer volume of available data makes advanced computer methods essen tial to analysis, and a familiarity with computers and sequence analy sis software a vital requirement for the researcher involved with DNA sequencing. Even for nonsequencers, a familiarity with sequence analysis software can be important. For instance, gene sequences already present in the databases can be extremely useful in the design of cloning and genetic manipulation experiments. This two-part work on Computer Analysis of Sequence Data is designed to be a practical aid to the researcher who uses computers for the acquisition, storage, or analysis of nucleic acid (and/or pro tein) sequences. Each chapter is written such that a competent scien tist with basic computer literacy can carry out the procedure successfully at the first attempt by simply following the detailed prac tical instructions that have been described by the author. A Notes section, which is included at the end of each chapter, provides advice on overcoming the common problems and pitfalls sometimes encoun tered by users of the sequence analysis software.

Computer Analysis of Sequence Data

Author: Annette M. Griffin

Publisher: Humana Press

Published: 1994-02-23

Total Pages: 392

ISBN-13: 9780896032460

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These comprehensive, up-to-date handbooks are designed for those scientists engaged in the computer analysis of sequence data who want hands-on help in using the most important commercial software available, but simply do not have the time to become computer experts. The expert authors guide you through the programs with easy-to-follow, step-by-step instructions. The topics covered include translations of sequences, sequence alignment, phylogenetic trees, analysis of RNA secondary structure, database searching, submission of data to EMBL/GenBank/DDBJ/etc., maintaining sequence projects, and using patterns to analyze protein sequences. Many chapters have been written by world-class authorities in the field, among them R. Staden, M. Gribskov, D. Higgins, W. Pearson, M. Zuker, and G. Barton. Each volume shares five essential chapters concerning the analysis of sequence data, the FASTA program, converting between sequence formats, obtaining software via INTERNET, and the submission of nucleotide sequence data. Part I covers GCG, MicroGenie, PC/GENE, and FASTA programs. Part II covers Staden and Staden Plus, DNA Strider, FASTA, and MacVector programs.

Computer Analysis of Sequence Data

Author: Annette M. Griffin

Publisher: Humana Press

Published: 1994-02-08

Total Pages: 445

ISBN-13: 9780896032767

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Computer Analysis of Sequence Data: Computer analysis of sequence data

Author: Annette M. Griffin

Publisher:

Published: 1994

Total Pages: 0

ISBN-13:

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Biological Sequence Analysis

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.

Sequence Data Analysis Guidebook

Author: Simon R. Swindell

Publisher: Humana

Published: 2013-08-17

Total Pages: 324

ISBN-13: 9781489943385

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Computers have revolutionized the analysis of sequencing data. It is unlikely that any sequencing projects have been performed in the last few years without the aid of computers. Recently their role has taken a further major step forward. Computers have become smaller and more powerful and the software has become simpler to use as it has grown in sophistication. This book reflects that change since the majority of packages described here are designed to be used on desktop computers. Computer software is now available that can run gels, collect data, and assess its accuracy. It can assemble, align, or compare multiple fragments, perform restriction analyses, identify coding regions and specific motifs, and even design the primers needed to extend the sequencing. Much of this soft ware may now be used on relatively inexpensive computers. It is now possible to progress from isolate d DNA to database submission without writing a single base down. To reflect this progression, the chapters in our Sequence Data Analysis Guidebook are arranged, not by software package, but by fimction. The early chapters deal with examining the data produced by modem automated sequenc ers, assessing its quality, and removing extraneous data. The following chap ters describe the process of aligning multiple sequences in order to assemble overlapping fragments into sequence contigs to compare similar sequences from different sources. Subsequent chapters describe procedures for compar ing the newly derived sequence to the massive amounts of information in the sequence databases.

DNA and Protein Sequence Analysis

Author: Martin J. Bishop

Publisher: IRL Press

Published: 1997

Total Pages: 384

ISBN-13:

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Sequence data--either lists of nucleotides or of amino acids--are now easily gathered using automated equipment; the real effort is involved in interpreting the data to produce predictions of protein structure or function. With the advent of worldwide computer networks, a plethora of software is now available for sequence analysis. This book describes the techniques for computer analysis of sequence data, with the emphasis on general issues rather than specific algorithms. Unlike many books on these topics, which focus on the "how-to" aspects of software packages, this one places more emphasis on the science behind the packages and on interpretation of the results.

Sequence Data Mining

Author: Guozhu Dong

Publisher: Springer Science & Business Media

Published: 2007-10-31

Total Pages: 160

ISBN-13: 0387699376

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Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Sequence — Evolution — Function

Author: Eugene V. Koonin

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 482

ISBN-13: 1475737831

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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.