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A topological data analytic approach for discovering biophysical signatures in protein dynamics

W. Tang, G. da Silva, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, K. Yang, S. Mukherjee, B. Rubenstein, and L. Crawford. PLoS Comput. Biol., 18 (5): e1010045 (May 2022)

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Gibbs posterior convergence and the thermodynamic formalismK. McGoff, S. Mukherjee, and A. Nobel. Ann. Appl. Probab., (February 2022)Ergodic Theorems for Dynamic Imprecise Probability KinematicsM. Caprio, and S. Mukherjee. (2022)Concentration inequalities and optimal number of layers for stochastic deep neural networksM. Caprio, and S. Mukherjee. (2023)Bayesian Multinomial Logistic Normal Models through Marginally Latent Matrix-T ProcessesJ. Silverman, K. Roche, Z. Holmes, L. David, and S. Mukherjee. Journal of Machine Learning Research, 23 (7): 1--42 (2022)Generalized Bayes approach to inverse problems with model misspecificationY. Baek, W. Aquino, and S. Mukherjee. Inverse Problems, 39 (10): 105011 (September 2023)The bulk and the extremes of minimal spanning acycles and persistence diagrams of random complexesN. Fraiman, S. Mukherjee, and G. Thoppe. (2020)A Bayesian hierarchical model to estimate DNA methylation conservation in colorectal tumorsK. Murgas, Y. Ma, L. Shahidi, S. Mukherjee, A. Allen, D. Shibata, and M. Ryser. Bioinformatics, 38 (1): 22--29 (September 2021)Learning Subspaces of Different DimensionsB. Thomas, K. You, L. Lin, L. Lim, and S. Mukherjee. Journal of Computational and Graphical Statistics, 31 (2): 337--350 (2022)Higher Order Bipartiteness vs Bi-Partitioning in Simplicial ComplexesM. Eidi, and S. Mukherjee. (2024)A sheaf-theoretic construction of shape spaceS. Arya, J. Curry, and S. Mukherjee. (2022)

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A topological data analytic approach for discovering biophysical signatures in protein dynamics

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A topological data analytic approach for discovering biophysical signatures in protein dynamics

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A topological data analytic approach for discovering biophysical signatures in protein dynamics