Search Results - "Husic, Brooke E."

Unsupervised Learning Methods for Molecular Simulation Data by Glielmo, Aldo, Husic, Brooke E, Rodriguez, Alex, Clementi, Cecilia, Noé, Frank, Laio, Alessandro

“…Unsupervised learning is becoming an essential tool to analyze the increasingly large amounts of data produced by atomistic and molecular simulations, in…”
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MSMBuilder: Statistical Models for Biomolecular Dynamics by Harrigan, Matthew P., Sultan, Mohammad M., Hernández, Carlos X., Husic, Brooke E., Eastman, Peter, Schwantes, Christian R., Beauchamp, Kyle A., McGibbon, Robert T., Pande, Vijay S.

“…MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis…”
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PotentialNet for Molecular Property Prediction by Feinberg, Evan N, Sur, Debnil, Wu, Zhenqin, Husic, Brooke E, Mai, Huanghao, Li, Yang, Sun, Saisai, Yang, Jianyi, Ramsundar, Bharath, Pande, Vijay S

“…The arc of drug discovery entails a multiparameter optimization problem spanning vast length scales. The key parameters range from solubility (angstroms) to…”
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Machine learning coarse-grained potentials of protein thermodynamics by Majewski, Maciej, Pérez, Adrià, Thölke, Philipp, Doerr, Stefan, Charron, Nicholas E., Giorgino, Toni, Husic, Brooke E., Clementi, Cecilia, Noé, Frank, De Fabritiis, Gianni

“…A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the…”
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Modeling the mechanism of CLN025 beta-hairpin formation by McKiernan, Keri A, Husic, Brooke E, Pande, Vijay S

“…Beta-hairpins are substructures found in proteins that can lend insight into more complex systems. Furthermore, the folding of beta-hairpins is a valuable test…”
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Optimized parameter selection reveals trends in Markov state models for protein folding by Husic, Brooke E, McGibbon, Robert T, Sultan, Mohammad M, Pande, Vijay S

“…As molecular dynamics simulations access increasingly longer time scales, complementary advances in the analysis of biomolecular time-series data are…”
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Simultaneous coherent structure coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity by Husic, Brooke E, Schlueter-Kuck, Kristy L, Dabiri, John O

“…The clustering of data into physically meaningful subsets often requires assumptions regarding the number, size, or shape of the subgroups. Here, we present a…”
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Markov State Models: From an Art to a Science by Husic, Brooke E, Pande, Vijay S

“…Markov state models (MSMs) are a powerful framework for analyzing dynamical systems, such as molecular dynamics (MD) simulations, that have gained widespread…”
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Identification of simple reaction coordinates from complex dynamics by McGibbon, Robert T, Husic, Brooke E, Pande, Vijay S

“…Reaction coordinates are widely used throughout chemical physics to model and understand complex chemical transformations. We introduce a definition of the…”
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Ward Clustering Improves Cross-Validated Markov State Models of Protein Folding by Husic, Brooke E, Pande, Vijay S

“…Markov state models (MSMs) are a powerful framework for analyzing protein dynamics. MSMs require the decomposition of conformation space into states via…”
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Deeptime: a Python library for machine learning dynamical models from time series data by Hoffmann, Moritz, Scherer, Martin, Hempel, Tim, Mardt, Andreas, de Silva, Brian, Husic, Brooke E, Klus, Stefan, Wu, Hao, Kutz, Nathan, Brunton, Steven L, Noé, Frank

“…Abstract Generation and analysis of time-series data is relevant to many quantitative fields ranging from economics to fluid mechanics. In the physical…”
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A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models by Husic, Brooke E, McKiernan, Keri A, Wayment-Steele, Hannah K, Sultan, Mohammad M, Pande, Vijay S

“…Markov state models (MSMs) are a powerful framework for the analysis of molecular dynamics data sets, such as protein folding simulations, because of their…”
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Understanding how Beta-Hairpins Fold using Molecular Dynamics Simulations in Multiple Force Fields by Husic, Brooke E., McKiernan, Keri A., Pande, Vijay S.

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Energy Landscapes for Proteins: From Single Funnels to Multifunctional Systems by Röder, Konstantin, Joseph, Jerelle A., Husic, Brooke E., Wales, David J.

“…This report advances the hypothesis that multifunctional systems may be associated with multifunnel potential and free energy landscapes, with particular focus…”
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Deference Done Better by Dorst, Kevin, Levinstein, Benjamin A., Salow, Bernhard, Husic, Brooke E., Fitelson, Branden

“…There are many things—call them ‘experts'—that you should defer to in forming your opinions. The trouble is, many experts are modest: they're less than certain…”
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Hierarchical Clustering of Markov State Models Reveals Sequence Effects in p53-CTD Dynamic Behavior by Wayment-Steele, Hannah K., Hernandez, Carlos X., Husic, Brooke E., Pande, Vijay S.

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Modeling and Interpreting Molecular Kinetics from Simulation Data by Husic, Brooke E

“…Atomistic simulations provide detailed information about a molecular system's dynamics at finer time and length scales than experiments can access. However,…”
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Osprey: Hyperparameter Optimization for Machine Learning by T. McGibbon, Robert, X. Hernández, Carlos, P. Harrigan, Matthew, Kearnes, Steven, M. Sultan, Mohammad, Jastrzebski, Stanislaw, E. Husic, Brooke, S. Pande, Vijay

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Deflation reveals dynamical structure in nondominant reaction coordinates by Husic, Brooke E, Noé, Frank

“…The output of molecular dynamics simulations is high-dimensional, and the degrees of freedom among the atoms are related in intricate ways. Therefore, a…”
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Machine Learning Implicit Solvation for Molecular Dynamics by Chen, Yaoyi, Krämer, Andreas, Charron, Nicholas E, Husic, Brooke E, Clementi, Cecilia, Noé, Frank

“…J. Chem. Phys. 155, 084101 (2021) Accurate modeling of the solvent environment for biological molecules is crucial for computational biology and drug design. A…”
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