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Enabling Protein Structure Prediction with Artificial Intelligence at Rutgers and Beyond

11/18

Enabling Protein Structure Prediction with Artificial Intelligence at Rutgers and BeyondEnabling Protein Structure Prediction with Artificial Intelligence at Rutgers and Beyond

Thursday, December 9 2021 | 1:00pm - 6:00pm ET

Register for this virtual event at go.rutgers.edu/dlqx9nfb

Download Program

  • Introductions: Stephen K. Burley, M.D., D.Phil.: Founding Director, Institute for Quantitative Biomedicine; J. Barr von Oehsen, Ph.D.: Associate Vice President, Office of Advanced Research Computing
  • Welcome and Crash Course Learning Objectives: Michael E. Zwick, Ph.D.: Senior Vice President, Office of Research
  • De Novo Protein Structure Prediction: Disruptive Transformation of Biology in 3D: Minkyung Baek, Ph.D.: University of Washington
  • Primer on Artificial Intelligence: Statistical Underpinning and Vocabulary: Sijian Wang, Ph.D.: IQB; SAS-Statistics
  • Potential for Impact on Research in Cell/Molecular, Cancer, and Structural Biology: Stephen K. Burley, M.D., D.Phil.: RCSB PDB; IQB; SAS-CCB; CINJ
  • Experience with Applications in Single-particle Cryo-Electron Microscopy: Vasileios Petrou, Ph.D.: CII; RNJMS-MB&MG
  • Experience with Applications in Computational Biology: Guillaume Lamoureux, Ph.D.: CCIB; CCAS-Chemistry
  • Experience with Applications in SARS-CoV-2 Protease Modeling and Drug Discovery: Sagar Khare, Ph.D.: IQB; SAS-CCB; CINJ
  • Primer: Getting Access to Rutgers Infrastructure (Amarel, AlphaFold2, RoseTTAFold): Balamurugan Desinghu, Ph.D.: OARC
  • Hands On De Novo Protein Structure Prediction Tutorial

QUESTIONS? Contact Michelle Sanghera msanghera@iqb.rutgers.edu

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