Modeling transcriptional regulation : methods and protocols /

Modeling transcriptional regulation : methods and protocols /

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Bibliographic Details
Imprint:New York : Humana Press, [2021]
©2021
Description:1 online resource (xi, 307 pages) : illustrations (some color)
Language:English
Series:Methods in molecular biology, 1064-3745 ; [2328]
Methods in molecular biology (Clifton, N.J.) ; v. 2328.
Subject:
Genetic transcription -- Regulation.
Genetic transcription -- Regulation
Laboratory manuals.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12616888
Hidden Bibliographic Details
Other authors / contributors:Mukhtar, Shahid M., editor.
ISBN:9781071615348
1071615343
9781071615331
Notes:Includes index.
Online resource; title from PDF title page (SpringerLink, viewed July 30, 2021).
Summary:This book provides methods and techniques used in construction of global transcriptional regulatory networks in diverse systems, various layers of gene regulation and mathematical as well as computational modeling of transcriptional gene regulation. 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, Modeling Transcriptional Regulation: Methods and Protocols aims to provide an in depth understanding of new techniques in transcriptional gene regulation for specialized audience.
Standard no.:10.1007/978-1-0716-1534-8
Table of Contents:
  • Co-expression Networks in Predicting Transcriptional Gene Regulation
  • Inference of Gene Coexpression Networks from Bulk-based RNA-Sequencing Data
  • Genomic Footprinting Analyses from DNase-seq data to Construct Gene Regulatory Networks
  • Spatiotemporal Gene Expression Profiling and Network Inference: A Roadmap For Analysis, Visualization, and Key Gene Identification
  • Dynamic Modeling of Transcriptional Gene Regulatory Networks- Mathematical Programming for Modelling Expression of a Gene using Gurobi Optimizer to Identify its Transcriptional Regulators
  • Multiscale Modeling of Cross-Regulatory Transcript and Protein Influences
  • Biological Network Mining
  • Identification of Gene Regulatory Networks from Single-Cell Expression Data- Inference of Gene Regulatory Network From Single-Cell Transcriptomic Data using pySCENIC
  • Modeling Immune Dynamics in Plants using JIMENA-package
  • Dynamic Regulatory Event Mining by iDREM in Large Scale Multi-Omics Datasets during Biotic and Abiotic Stress in Plants
  • A semi-in vivo Transcriptional Assay to Dissect Plant Defense Regulatory Modules
  • Assessing Global Circadian Rhythm through Single-Time-Point Transcriptomic Analysis
  • High-throughput Targeted Transcriptional Profiling of Defense Genes using RNA-mediated oligonucleotide Annealing, Selection, and Ligation with next-generation sequencing in Arabidopsi
  • Rapid Validation of Transcriptional Enhancers Using a Transient Reporter Assay
  • Computational Identification of ceRNA and Reconstruction of ceRNA Regulatory Network Based on RNA-seq and Small RNA-seq Data in Plants
  • In Silico Prediction for ncRNAs in Prokaryotes
  • Mathematical Linear Programming to Model MicroRNAs-Mediated Gene Regulation Using Gurobi Optimizer.

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