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Hi-C Data Analysis: Methods and Protocols 2021 ed. [Kõva köide]

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  • Formaat: Hardback, 354 pages, kõrgus x laius: 254x178 mm, kaal: 889 g, 58 Illustrations, color; 4 Illustrations, black and white; XIII, 354 p. 62 illus., 58 illus. in color. With online files/update., 1 Hardback
  • Sari: Methods in Molecular Biology 2301
  • Ilmumisaeg: 21-Aug-2021
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1071613898
  • ISBN-13: 9781071613894
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Hi-C Data Analysis: Methods and Protocols 2021 ed.Suurem pilt
  • Formaat: Hardback, 354 pages, kõrgus x laius: 254x178 mm, kaal: 889 g, 58 Illustrations, color; 4 Illustrations, black and white; XIII, 354 p. 62 illus., 58 illus. in color. With online files/update., 1 Hardback
  • Sari: Methods in Molecular Biology 2301
  • Ilmumisaeg: 21-Aug-2021
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1071613898
  • ISBN-13: 9781071613894
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781071613894.html
Märksõnad:

This volume details a comprehensive set of methods and tools for Hi-C data processing, analysis, and interpretation. Chapters cover applications of Hi-C to address a variety of biological problems, with a specific focus on state-of-the-art computational procedures adopted for the data analysis. 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, Hi-C Data Analysis: Methods and Protocols aims to help computational and molecular biologists working in the field of chromatin 3D architecture and transcription regulation.

Normalization of Chromosome Contact Maps: Matrix Balancing and
Visualization.- Methods to Assess the Reproducibility and Similarity of Hi-C
Data.- Methods for the Analysis of Topological Associating Domains
(TADs).- Methods for the Differential Analysis of Hi-C D.- Visualising and
Annotating Hi-C Data.- Hi-C Data Formats.- Analysis of Hi-C Data for
Discovery of Structural Variations In Cancer.- Metagenomes Binning using
Proximity-Ligation Data.- Generating High-resolution Hi-C Contact Maps Of
Bacteria.- Computational Tools for the Multiscale Analysis of HiC Data in
Bacterial Chromosomes.- Analysis of HiChIP Data.- The Physical Behavior of
Interphase Chromosomes: Polymer Theory and Coarse-Grain Computer
Simulations.- Polymer Folding Simulations from Hi-C Data.- Predictive Polymer
Models for 3D Chromosome Organization.- Polymer Modeling of 3D Epigenome
Folding: Application to Drosophila.- A Polymer Physics Model To Dissect
Genome Organization In Healthy And Pathological Phenotypes.- The 3D
Organization of Chromatin Colors in Mammalian Nuclei.- Modeling the 3D Genome
using Hi-C and Nuclear Lamin-Genome Contacts.