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Deep Sequencing Data Analysis Second Edition 2021 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 374 pages, height x width: 254x178 mm, weight: 728 g, 81 Illustrations, color; 11 Illustrations, black and white; X, 374 p. 92 illus., 81 illus. in color., 1 Paperback / softback
  • Sērija : Methods in Molecular Biology 2243
  • Izdošanas datums: 20-Feb-2022
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071611054
  • ISBN-13: 9781071611050
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  • Mīkstie vāki
  • Cena: 118,31 €*
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Deep Sequencing Data Analysis Second Edition 2021Palielināt
  • Formāts: Paperback / softback, 374 pages, height x width: 254x178 mm, weight: 728 g, 81 Illustrations, color; 11 Illustrations, black and white; X, 374 p. 92 illus., 81 illus. in color., 1 Paperback / softback
  • Sērija : Methods in Molecular Biology 2243
  • Izdošanas datums: 20-Feb-2022
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071611054
  • ISBN-13: 9781071611050
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781071611050.html
Keywords:

This second edition provides new and updated chapters from expert researchers in the field detailing methods used to study the multi-facet deep sequencing data field. Chapters guide readers through techniques for processing RNA-seq data, microbiome analysis, deep learning methodologies, 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 the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

 Authoritative and cutting-edge, Deep Sequencing Data Analysis: Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field.

Detecting Causal Variants in Mendelian Disorders using Whole Genome
Sequencing.- Statistical Considerations on NGS Data for Inferring Copy Number
Variations.- Applications of Community Detection Algorithms to Large
Biological Datasets.- Processing and Analysis of RNA-seq data from Public
Resources.- Improved Analysis of High-throughput Sequencing Data Using Small
Universal k-mer Hitting Sets.- An Introduction to Whole-metagenome Shotgun
Sequencing Studies.- Microbiome Analysis using 16S Amplicon Sequencing: From
Samples to ASVs.- RNA-Seq in Non-model Organisms.- Deep Learning Applied on
Next Generation Sequencing Data Analysis.- Interrogating the Accessible
Chromatin Landscape of Eukaryote Genomes using ATAC-seq.- Genome-Wide
Noninvasive Prenatal Diagnosis of SNPs and Indels.- Genome-wide Noninvasive
Prenatal Diagnosis of De Novo Mutations.- Accurate Imputation of Untyped
Variants from Deep Sequencing Data.- Multi-region Sequence Analysisto Predict
Intratumor Heterogeneity and Clonal Evolution.- Overcoming Interpretability
in Deep Learning Cancer Classification.- Single-cell Transcriptome
Profiling.- Biological Perspectives of RNA-sequencing Experimental
Design.- Analysis of microRNA Regulation in Single Cells.- DNA Data
Collection and Analysis in the Forensic Arena.