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© Research
Publication : Computational and structural biotechnology journal

Computational biology approaches for mapping transcriptional regulatory networks.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Computational and structural biotechnology journal - 01 Jan 2021

Saint-André V,

Link to Pubmed [PMID] – 34522292

Link to DOI – 10.1016/j.csbj.2021.08.028

Comput Struct Biotechnol J 2021 ; 19(): 4884-4895

Transcriptional Regulatory Networks (TRNs) are mainly responsible for the cell-type- or cell-state-specific expression of gene sets from the same DNA sequence. However, so far there are no precise maps of TRNs available for each cell-type or cell-state, and no ideal tool to map those networks clearly and in full from biological samples. In this review, major approaches and tools to map TRNs from high-throughput data are presented, depending on the type of methods or data used to infer them, and their advantages and limitations are discussed. After summarizing the main principles defining the topology and structure–function relationships in TRNs, an overview of the extensive work done to map TRNs from bulk transcriptomic data will be presented by type of methodological approach. Most recent modellings of TRNs using other types of molecular data or integrating different data types, including single-cell RNA-sequencing and chromatin information, will then be discussed, before briefly concluding with improvements expected to come in the field.