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Life Sciences - Systems Biology and Bioinformatics | Deep Sequencing Data Analysis

Deep Sequencing Data Analysis

Series: Methods in Molecular Biology, Vol. 1038

Shomron, Noam (Ed.)

2013, X, 234 p. 81 illus., 43 illus. in color.

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  • Includes cutting-edge methods and protocols in the MiMB standard format
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

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.

Content Level » Professional/practitioner

Keywords » Chromatin Immunoprecipitation (ChIP-seq) - Reverse Transcriptase Termination Site (RTTS) - alternative mRNA splicing - data analysis - deep sequencing - deep sequencing data analysis - genetic sequence - microRNAs - nucleic acids - sequencing outputs - ‘Exome’ information

Related subjects » Human Genetics - Systems Biology and Bioinformatics

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