11 citations · 26 across the 6 of their papers we have counts for
6 papers
No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology
Luka Kovačević, Thomas Gaudelet, James Opzoomer +5
Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucidating regulatory biology, particularly in the realm of predicting gene expression…
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
Peter St. John, Dejun Lin, Polina Binder +89
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increas…
Season combinatorial intervention predictions with Salt & Peper
Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami +4
Interventions play a pivotal role in the study of complex biological systems. In drug discovery, genetic interventions (such as CRISPR base editing) have become central to both ide…
PyRelationAL: a python library for active learning research and development
Paul Scherer, Alison Pouplin, Alice Del Vecchio +6
Active learning (AL) is a sub-field of ML focused on the development of methods to iteratively and economically acquire data by strategically querying new data points that are the…
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro
Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma +17
For large libraries of small molecules, exhaustive combinatorial chemical screens become infeasible to perform when considering a range of disease models, assay conditions, and dos…
Utilising Graph Machine Learning within Drug Discovery and Development
Thomas Gaudelet, Ben Day, Arian R. Jamasb +11
Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional r…