Machine Learning for Biomolecular Design and Simulation
FOCUS · C04 · ID: 381261
Presentations
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Rational optimization of drug-membrane selectivity by computational screening
ORAL
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Presenters
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Bernadette Mohr
- Van ‘t Hoff Institute for Molecular Sciences, Informatics Institute, University of Amsterdam
Authors
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Bernadette Mohr
- Van ‘t Hoff Institute for Molecular Sciences, Informatics Institute, University of Amsterdam
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Kirill Shmilovich
- Pritzker School of Molecular Engineering, University of Chicago
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Tristan Bereau
- University of Amsterdam
- Van 't Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam
- Van ‘t Hoff Institute for Molecular Sciences, Informatics Institute, University of Amsterdam
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Andrew Ferguson
- University of Chicago
- Pritzker School of Molecular Engineering, University of Chicago
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Learning molecular models from simulation and experimental data
Invited
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Presenters
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Cecilia Clementi
- Rice Univ
- Physics, Freie Universität Berlin
Authors
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Cecilia Clementi
- Rice Univ
- Physics, Freie Universität Berlin
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Toward Transferable Deep Learning Atomistic Potential for Biomolecular Simulations
ORAL
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Presenters
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Olexandr Isayev
- Carnegie Mellon Univ
Authors
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Olexandr Isayev
- Carnegie Mellon Univ
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Accurate Molecular Polarizabilities with Coupled Cluster Theory and Machine Learning
ORAL
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Presenters
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Yang Yang
- Chemistry and Chemical Biology, Cornell University
- Department of Chemistry and Chemical Biology, Cornell University
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY
Authors
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Yang Yang
- Chemistry and Chemical Biology, Cornell University
- Department of Chemistry and Chemical Biology, Cornell University
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY
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Ka Un Lao
- Department of Chemistry and Chemical Biology, Cornell University
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David M. Wilkins
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne
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Andrea Grisafi
- École Polytechnique Federale de Lausanne
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne
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Michele Ceriotti
- Ecole polytechnique federale de Lausanne
- Ecole Polytechnique Federale de Lausanne
- Institute of Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland
- École Polytechnique Federale de Lausanne
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne
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Robert Distasio
- Chemistry and Chemical Biology, Cornell University
- Department of Chemistry and Chemical Biology, Cornell University
- Cornell University
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY
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Machine Learning on a Quantum Hamiltonian shows that DNA is Much Stretchier than Classical Simulations Suggest
ORAL
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Presenters
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Joshua Berryman
- University of Luxembourg Limpertsberg
Authors
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Joshua Berryman
- University of Luxembourg Limpertsberg
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Machine learning for DNA self-assembly: a numerical case study
ORAL
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Presenters
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Jörn Appeldorn
- Institute of Physics, Johannes Gutenberg University Mainz
Authors
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Jörn Appeldorn
- Institute of Physics, Johannes Gutenberg University Mainz
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Arash Nikoubashman
- University of Mainz
- Department of Physics, University of Mainz
- Johannes Gutenberg University
- Institute of Physics, Johannes Gutenberg University Mainz
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Thomas Speck
- Institute of Physics, Johannes Gutenberg University Mainz
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Predicting Protein Developability via Convolutional Sequence Representation
ORAL
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Presenters
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Alexander Golinski
- University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnnesota
Authors
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Alexander Golinski
- University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnnesota
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Bryce Johnson
- University of Minnesota
- School of Physics and Astronomy, University of Minnesota
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Sidharth Laxminarayan
- University of Minnesota
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Diya Saha
- University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnnesota
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Sandhya Appiah
- University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnnesota
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Benjamin Hackel
- University of Minnesota
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Stefano Martiniani
- University of Minnesota
- Chemical Engineering and Materials Science, University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnesota
- Department of Chemical Engineering and Materials Science, University of Minnnesota
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Supremum modeling to extend model transferability in systems biology
ORAL
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Presenters
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Cody Petrie
- Brigham Young University
Authors
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Cody Petrie
- Brigham Young University
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Christian Anderson
- Brigham Young University
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Mark Transtrum
- Physics and Astronomy, Brigham Young University
- Brigham Young University
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Prospective experimental validation of machine learning for biological sequence design
Invited
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Presenters
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Lucy Colwell
- Univ of Cambridge
Authors
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Lucy Colwell
- Univ of Cambridge
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Recurrent networks for protein structure prediction using Frenet-Serret equations and latent residue representations
ORAL
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Presenters
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Nazim Bouatta
- Harvard Medical School
Authors
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Nazim Bouatta
- Harvard Medical School
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Multi-fidelity integrated computational-experimental design of self-assembling π-conjugated optoelectronic peptides
ORAL
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Presenters
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Kirill Shmilovich
- University of Chicago
Authors
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Kirill Shmilovich
- University of Chicago
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Sayak Panda
- Johns Hopkins University
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John D. Tovar
- Johns Hopkins University
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Andrew Ferguson
- University of Chicago
- Pritzker School of Molecular Engineering, University of Chicago
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