Description

Book Synopsis
Mapping the genomic landscapes is one of the most exciting frontiers of science. We have the opportunity to reverse engineer the blueprints and the control systems of living organisms. Computational tools are key enablers in the deciphering process. This book provides an in-depth presentation of some of the important computational biology approaches to genomic sequence analysis. The first section of the book discusses methods for discovering patterns in DNA and RNA. This is followed by the second section that reflects on methods in various ways, including performance, usage and paradigms.

Table of Contents
Pattern Discovery Methods: Large-Scale Gene Regulatory Motif Discovery with NestedMICA (M Piipari et al.); R'MES: A Tool to Find Motifs with a Significantly Unexpected Frequency in Biological Sequences (S Schbath & M Hoebeke); An Intricate Mosaic of Genomic Patterns at Mid-range Scale (A Fedorov & L Fedorova); Motif Finding from Chips to ChIPs (G Pavesi); A New Approach to the Discovery of RNA Structural Elements in the Human Genome (L Hua et al.); Performance and Paradigms: Benchmarking of Methods for Motif Discovery in DNA (K Klepper et al.); Encyclopedias of DNA elements for Plant Genomes (J Lichtenberg et al.); Manycore High-Performance Computing in Bioinformatics (J-S Varre et al.); Natural Selection and the Genome (A L Hughes).

Advances In Genomic Sequence Analysis And Pattern

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A Hardback by Laura Elnitski, Lonnie R Welch, Helen Piontkivska

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    View other formats and editions of Advances In Genomic Sequence Analysis And Pattern by Laura Elnitski

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 20/01/2011
    ISBN13: 9789814327725, 978-9814327725
    ISBN10: 9814327727

    Description

    Book Synopsis
    Mapping the genomic landscapes is one of the most exciting frontiers of science. We have the opportunity to reverse engineer the blueprints and the control systems of living organisms. Computational tools are key enablers in the deciphering process. This book provides an in-depth presentation of some of the important computational biology approaches to genomic sequence analysis. The first section of the book discusses methods for discovering patterns in DNA and RNA. This is followed by the second section that reflects on methods in various ways, including performance, usage and paradigms.

    Table of Contents
    Pattern Discovery Methods: Large-Scale Gene Regulatory Motif Discovery with NestedMICA (M Piipari et al.); R'MES: A Tool to Find Motifs with a Significantly Unexpected Frequency in Biological Sequences (S Schbath & M Hoebeke); An Intricate Mosaic of Genomic Patterns at Mid-range Scale (A Fedorov & L Fedorova); Motif Finding from Chips to ChIPs (G Pavesi); A New Approach to the Discovery of RNA Structural Elements in the Human Genome (L Hua et al.); Performance and Paradigms: Benchmarking of Methods for Motif Discovery in DNA (K Klepper et al.); Encyclopedias of DNA elements for Plant Genomes (J Lichtenberg et al.); Manycore High-Performance Computing in Bioinformatics (J-S Varre et al.); Natural Selection and the Genome (A L Hughes).

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