Statistical Genomics: Methods and Protocols: Methods in Molecular Biology, cartea 1418
Editat de Ewy Mathé, Sean Davisen Limba Engleză Hardback – 24 mar 2016
Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 775.96 lei 43-57 zile | |
Springer – 19 apr 2018 | 775.96 lei 43-57 zile | |
Hardback (1) | 846.38 lei 43-57 zile | |
Springer – 24 mar 2016 | 846.38 lei 43-57 zile |
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Specificații
ISBN-13: 9781493935765
ISBN-10: 1493935763
Pagini: 350
Ilustrații: XI, 418 p. 113 illus., 85 illus. in color.
Dimensiuni: 178 x 254 x 24 mm
Greutate: 0.96 kg
Ediția:1st ed. 2016
Editura: Springer
Colecția Humana
Seria Methods in Molecular Biology
Locul publicării:New York, NY, United States
ISBN-10: 1493935763
Pagini: 350
Ilustrații: XI, 418 p. 113 illus., 85 illus. in color.
Dimensiuni: 178 x 254 x 24 mm
Greutate: 0.96 kg
Ediția:1st ed. 2016
Editura: Springer
Colecția Humana
Seria Methods in Molecular Biology
Locul publicării:New York, NY, United States
Public țintă
Professional/practitionerCuprins
Overview of Sequence Data Formats.- Integrative Exploratory Analysis of Two or More Genomic Datasets.- Study Design for Sequencing Studies.- Genomic Annotation Resources in R/Bioconductor.- The Gene Expression Omnibus Database.- A Practical Guide to the Cancer Genome Atlas (TCGA).- Working with Oligonucleotide Arrays.- Meta-Analysis in Gene Expression Studies.- Practical Analysis of Genome Contact Interaction Experiments.- Quantitative Comparison of Large-Scale DNA Enrichment Sequencing Data.- Variant Calling From Next Generation Sequence Data.- Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes.- NGS-QC Generator: A Quality Control System for ChIP-seq and Related Deep Sequencing-Generated Datasets.- Operating on Genomic Ranges Using BEDOPS.- GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality.- Visualizing Genomic Data using Gviz and Bioconductor.- Introducing Machine Learning Concepts with WEKA.- Experimental Design and Power Calculation for RNA-Seq Experiments.- It’s DE-licious: A Recipe for Differential Expression Analyses of RNA-Seq Experiments Using Quasi-Likelihood Methods in EdgeR.
Recenzii
“This collection of articles offers a thorough overview of the field, making it an opportune and useful addition to the literature. The book is written in an accessible language and the variety of the topics which are presented recommends it as an excellent starting point or updated reference of the field. It is suitable for both post-graduate and established researchers, and the numerous examples that accompany the discussed topics recommend it as an asset.” (Irina Ioana Mohorianu, zbMATH 1346.92003, 2016)
Textul de pe ultima copertă
This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories, common applications, and representative tools for operating on genomic data. Statistical Genomics: Methods and Protocols is divided into four sections. The first section discusses overview material and resources that can be applied across topics mentioned throughout the book. The second section covers prominent public repositories for genomic data. The third section presents several different biological applications of statistical genomics, and the fourth section highlights software tools that can be used to facilitate ad hoc analysis and data integration. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible analysis protocols, and tips on troubleshooting and avoiding known pitfalls.
Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.
Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.
Caracteristici
Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts Includes supplementary material: sn.pub/extras