Automatic extraction of transcriptional regulatory interactions of bacteria from biomedical literature using a BERT-based approach.

Transcriptional regulatory networks (TRNs) give a global view of the regulatory mechanisms of bacteria to respond to environmental signals. These networks are published in biological databases as a valuable resource for experimental and bioinformatics researchers. Despite the efforts to publish TRNs of diverse bacteria, many of them still lack one and many of the existing TRNs are incomplete.

An Epistatic Network Describes and as Relevant Genes for .

is an acid-fast bacterium that causes tuberculosis worldwide. The role of epistatic interactions among different loci of the genome under selective pressure may be crucial for understanding the disease and the molecular basis of antibiotic resistance acquisition. Here, we analyzed polymorphic loci interactions by applying a model-free method for epistasis detection, SpydrPick, on a pan-genome-wide alignment created from a set of 254 complete reference genomes.