Includes cutting-edge methods and protocols

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts

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.