Fields- Workshop on the Mathematics of Drug Design/Discovery

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    Physiological Modeling of Heart Failure

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    Big Data and Biophysics

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    Integrating topology and machine learning for drug design and discovery

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    A pose prediction approach based on ligand 3D shape similarity

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    Cosolvent Molecular Dynamics Simulations

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    Accurate methods for protein-ligand binding free energies

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    Screening an almost unbounded chemical space for novel ligands with novel GPCR pharmacology

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    Targeting protein-DNA interactions with small molecules

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    Emerging challenges in targeting disordered proteins: Lessons learned from targeting p27

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    Modeling, Design and Engineering of Allosteric Regulatory Mechanisms Mediated by Molecular Chaperones in Signal Transduction Networks: An Integrative Platform of Computational Systems Biology, Network Science and Machine Learning Approaches

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    A Data-driven approach to drug discovery: from machine learning to deep learning

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    Computational Drug Design for Metastatic Bladder Cancer Using Tubulin as a Target

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    Manifold learning for virtual screening and drug-target binding affinity predictions

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    Challenges of Rapid Computational Protein Docking

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    High-Performance Computing and Computational Polypharmacology: Opportunities and Obstacles

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    How inhibitors bind to hSGLT sugar transporters.

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    Structure Conforming Continuum Modeling of Biomolecular Conformational Dynamics

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    Efficient sampling and optimization on manifolds for macromolecular docking

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