Filtering of Data-Driven Gene Regulatory Networks Using Drosophila melanogaster as a Case Study.

ABSTRACT: Gene Regulatory Networks (GRNs) allow the study of regulation of gene expression of whole genomes. Among the most relevant advantages of using networks to depict this key process, there is the visual representation of large amounts of information and the application of graph theory to generate new knowledge. Nonetheless, despite the many uses of GRNs, it is still difficult and expensive to assign Transcription Factors (TFs) to the regulation of specific genes. ChIP-Seq allows the determination of TF Binding Sites (TFBSs) over whole genomes, but it is still an expensive technique that can only be applied one TF at a time and requires replicates to reduce its noise. Once TFBSs are determined, the assignment of each TF and its binding sites to the regulation of specific genes is not trivial,

SUBMITTER: Cuesta-Astroz Y 

PROVIDER: S-EPMC8355599 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature