Machine Learning in Drug Discovery Symposium: Lightning Talks скачать в хорошем качестве

Machine Learning in Drug Discovery Symposium: Lightning Talks

Lightning Talks F.A.D.E. (Fully Agentic Drug Engine): A Conversational AI Platform for Drug Discovery Xue Zong Georgia Institute of Technology PostaNet: Ai-based Framework for Protein Stability Prediction with Experimental Validation Tianjian Liang University of Pittsburgh Genomic Language Models Decipher the Regulatory Code of Splicing for Drug Sensitivity Xueyang He University of Rochester ATLAS Breaks Data Scaling Barriers for MachineLearning via High-Throughput Synthesis and Screening Imran Haque Kimia Therapeutics The Machine Learning in Drug Discovery Symposium was held on November 7, 2025 at the Broad Institute. This hybrid symposium highlights recent progress in the application of machine learning techniques to drug discovery and brings together researchers working in applying machine learning to target validation, hit identification and optimization, clinical trial design, biologics, and other areas of drug discovery for talks, poster sessions and networking. For questions about the symposium or interest in sponsoring the 2026 symposium, reach out to mlinddsymposium@broadinstitute.org. For more information, visit: https://www.broadinstitute.org/machin... Copyright Broad Institute, 2025. All rights reserved.