Julio Collado‐Vides

The paper maps DNA binding of 139 E. coli TFs using ChIP-Seq and trains BoltzNet, a neural network that predicts TF binding energy from DNA sequence, validated with biophysical experiments.

This study identifies DicC, a cryptic prophage transcription factor in E. coli, and shows it regulates hundreds of host genes, influencing bacterial phenotypes independently of other prophage genes.

The paper analyzes the sources of evidence for transcription factor regulatory interactions in E. coli K-12, classifies them into seven groups, and evaluates confidence levels of interactions using high-throughput data.

Lisen&Curate is a system that aids manual curation of bacterial transcription initiation regulation by integrating text mining and sentence similarity metrics to accelerate literature review and knowledge extraction.

The paper introduces L-Regulon, a soft-curation approach using semantic enrichment to improve knowledge extraction from scientific literature, specifically applied to RegulonDB data.

PulmonDB provides a curated database and R library for exploring gene expression in COPD and IPF, enabling differential expression analysis and hypothesis generation.

GeDex extracts consensus gene-disease associations from biomedical literature using frequency patterns and supervised learning, achieving competitive performance compared to existing methods.

The paper shows that most transcription factors regulate genes involved in multiple biological processes, challenging the one TF/one process assumption.

The paper creates a similarity corpus for microbial transcriptional regulation sentences, evaluated by curators to aid in biomedical literature curation.

The paper identifies a comprehensive dataset of Crl-regulated genes in E. coli and traces the evolutionary history of the Crl regulon across archaeal and bacterial taxa.

The paper introduces MCO, an ontology for standardized annotation of microbial growth conditions, enabling comparison of gene expression data across experiments.

The paper expands RegulonDB to integrate high-throughput binding data with existing knowledge on gene regulation in E. coli K-12, enhancing its comprehensiveness and utility.