Computer Analysis of Sequence Data Part II

Computer Analysis of Sequence Data Part II PDF

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, Part I

Computer Analysis of Sequence Data, Part I PDF

Author: Annette M. Griffin

Publisher: Springer Science & Business Media

Published: 2008-02-02

Total Pages: 370

ISBN-13: 1592595111

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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.

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.

Computer Analysis of Sequence Data

Computer Analysis of Sequence Data PDF

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: Computer analysis of sequence data

Computer Analysis of Sequence Data: Computer analysis of sequence data PDF

Author: Annette M. Griffin

Publisher:

Published: 1994

Total Pages: 0

ISBN-13:

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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.

Sequence — Evolution — Function

Sequence — Evolution — Function PDF

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.

DNA and Protein Sequence Analysis

DNA and Protein Sequence Analysis PDF

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

Sequence Data Mining PDF

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.

Computational Genomics with R

Computational Genomics with R PDF

Author: Altuna Akalin

Publisher: CRC Press

Published: 2020-12-16

Total Pages: 462

ISBN-13: 1498781861

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Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.