Dr. Pedro J. Ballester: Machine Learning & Drug Discovery: A 15-Year Perspective скачать в хорошем качестве

Dr. Pedro J. Ballester: Machine Learning & Drug Discovery: A 15-Year Perspective

In this session of the BIDMaP Seminar Series, we explore the intersection of machine learning and structure-based drug discovery. Over the last decade and a half, data-driven approaches have fundamentally shifted how researchers identify and optimize potential new medicines. The Bakar Institute of Digital Materials for the Planet (BIDMaP) at UC Berkeley is dedicated to integrating chemistry, physics, and machine learning to solve global challenges. While BIDMaP focuses on materials for the planet, the computational methods used in drug discovery—such as scoring functions and molecular modeling—share a common foundation with the development of new materials for carbon capture and sustainable energy. This talk bridges those disciplines, demonstrating how AI can accelerate discovery across the molecular sciences. Featuring: Dr. Pedro J. Ballester, Royal Society Wolfson Fellow & Associate Professor at Imperial College London. Objective: This seminar highlights the evolution of machine-learning scoring functions and their transformative role in predicting molecular interactions. By providing a 15-year retrospective, Dr. Ballester offers critical insights into the reliability, challenges, and future potential of AI-driven molecular design—knowledge that is essential for researchers working at the cutting edge of both biotech and materials science. Hosted by: UC Berkeley’s Bakar Institute of Digital Materials for the Planet (BIDMaP). Learn more: To explore the Emerging Scholars series and stay updated on upcoming events, visit: https://bidmap.berkeley.edu/EmergingS...