Peter D’Eustachio

This paper applies large language models to assist in gene annotation into Reactome pathways, showing promising results in supporting curation workflows.

The paper annotates disease variants in the context of biological pathways to infer molecular phenotypes and model variant impacts.

The paper updates the Alliance of Genome Resources' central infrastructure, adding tools and enhancing data management and curation capabilities.

This paper explores using ChatGPT in Reactome curation to automate pathway annotation, comparing its outputs to manual curation and identifying challenges and improvements.

The paper converts human GO-CAMs to mouse GO-CAMs to link gene pathway perturbations with phenotypes, showing distinct outcomes from glycolysis and gluconeogenesis gene mutations.

The paper predicts functional interactions of dark proteins with Reactome pathways using a random forest classifier and develops a web portal to visualize these interactions.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.