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Hi-C Data Analysis
Details
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.
Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts
Inhalt
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.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Anzahl Seiten 368
- Herausgeber Springer US
- Gewicht 692g
- Untertitel Methods and Protocols
- Titel Hi-C Data Analysis
- Veröffentlichung 22.08.2022
- ISBN 1071613928
- Format Kartonierter Einband
- EAN 9781071613924
- Jahr 2022
- Größe H254mm x B178mm x T20mm
- Lesemotiv Verstehen
- Editor Francesco Ferrari, Silvio Bicciato
- Auflage 1st edition 2022
- GTIN 09781071613924