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Deep Sequencing Data Analysis 2013 ed. [Kõva köide]

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  • Formaat: Hardback, 234 pages, kõrgus x laius: 254x178 mm, kaal: 6075 g, 43 Illustrations, color; 38 Illustrations, black and white; X, 234 p. 81 illus., 43 illus. in color., 1 Hardback
  • Sari: Methods in Molecular Biology 1038
  • Ilmumisaeg: 20-Jul-2013
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1627035133
  • ISBN-13: 9781627035132
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Deep Sequencing Data Analysis 2013 ed.Suurem pilt
  • Formaat: Hardback, 234 pages, kõrgus x laius: 254x178 mm, kaal: 6075 g, 43 Illustrations, color; 38 Illustrations, black and white; X, 234 p. 81 illus., 43 illus. in color., 1 Hardback
  • Sari: Methods in Molecular Biology 1038
  • Ilmumisaeg: 20-Jul-2013
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1627035133
  • ISBN-13: 9781627035132
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781627035132.html
Märksõnad:

The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls.

Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.



This book details key data analysis procedures for deep sequencing data interpretation. It includes lists of necessary materials and reagents; step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls.

An Introduction to High-throughput Sequencing Experiments: Design and
Bioinformatics Analysis.- Compressing Resequencing Data with GReEn .- On the
Accuracy of Short Read Mapping.- Statistical Modeling of Coverage in
High-Throughput Data.- Assembly Algorithms for Deep Sequencing Data: Basics
and Pitfalls.- Short Reads Mapping for Exome Sequencing. ­Profiling Short
Tandem Repeats from Short Reads.- Exome Sequencing Analysis: A Guide to
Disease Variant Detection.- Identifying RNA Editing Sites in miRNAs by Deep
Sequencing.- Identifying Differential Alternative Splicing Events from RNA
Sequencing Data using RNASeq-MATS.- Optimizing Detection of Transcription
Factor Binding Sites in ChIP-seq Experiments.- Statistical Analysis of
ChIP-seq Data with MOSAiCS.- Detection of Reverse Transcriptase Termination
Sites using cDNA Ligation and Massive Parallel Sequencing.