papers
Publications (3)
cs.LG2026
Probabilistic Contrastive Pretraining for Multi-task ADME Property Prediction
Yifan Xue, Srimukh Prasad Veccham, Saee Paliwal +2
Accurate prediction of absorption, distribution, metabolism, and excretion (ADME) properties is critical to drug discovery, but remains challenging because ADME endpoints are noisy…
q-bio.GN2019
A multi-modal neural network for learning cis and trans regulation of stress response in yeast
Boxiang Liu, Nadine Hussami, Avanti Shrikumar +5
Deciphering gene regulatory networks is a central problem in computational biology. Here, we explore the use of multi-modal neural networks to learn predictive models of gene expre…
cs.LG2025
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…