8 papers
Large-scale AI-Ready Data for Anti-Cancer Drug Response Modeling
Vincent Lavelle, Yitan Zhu, Kaitlyn Marlor +2
Drug response prediction (DRP) models are an active area of research in pharmacogenomics, with growing potential to accelerate the identification of effective anticancer drugs. How…
Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization
Xuefeng Liu, Mingxuan Cao, Qinan Huang +3
Scientific reasoning is an increasingly important capability of large language models, yet improving the robustness and efficiency of training such reasoning remains a key open cha…
Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins
Matthew Sinclair, Moeen Meigooni, Archit Vasan +14
Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease -- approximately 80\% of cancer-related proteins contain lon…
BioAlchemy: Distilling Biological Literature into Reasoning-Ready Reinforcement Learning Training Data
Brian Hsu, Ozan Gökdemir, Carlo Siebenschuh +7
Despite the large corpus of biology training text, the impact of reasoning models on biological research generally lags behind math and coding. In this work, we show that biology q…
PRISM: Protocol Refinement through Intelligent Simulation Modeling
Brian Hsu, Priyanka V Setty, Rory M Butler +7
Automating experimental protocol design and execution remains as a fundamental bottleneck in realizing self-driving laboratories. We introduce PRISM (Protocol Refinement through In…
Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches
Xuefeng Liu, Songhao Jiang, Xiaotian Duan +14
Protein-ligand binding is the process by which a small molecule (drug or inhibitor) attaches to a target protein. Binding affinity, which characterizes the strength of biomolecular…