Structure primed embedding on the transcription factor manifold enables transparent model architectures for gene regulatory network and latent activity inference.

ABSTRACT: The modeling of gene regulatory networks (GRNs) is limited due to a lack of direct measurements of regulatory features in genome-wide screens. Most GRN inference methods are therefore forced to model relationships between regulatory genes and their targets with expression as a proxy for the upstream independent features, complicating validation and predictions produced by modeling frameworks. Separating covariance and regulatory influence requires aggregation of independent and complementary sets of evidence, such as transcription factor (TF) binding and target gene expression. However, the complete regulatory state of the system, e.g. TF activity (TFA) is unknown due to a lack of experimental feasibility, making regulatory relations difficult to infer. Some methods attempt to accou

SUBMITTER: Tjarnberg A 

PROVIDER: S-EPMC9915715 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature