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Retrosynthetic reaction prediction using neural sequence-to-sequence models., , , , , , , , , и . CoRR, (2017)Decision functions from supervised machine learning algorithms as collective variables for accelerating molecular simulations., и . CoRR, (2018)Progress and challenges in the automated construction of Markov state models for full protein systems, , , и . The Journal of Chemical Physics, (2009)Combining Mutual Information with Structural Analysis to Screen for Functionally Important Residues in Influenza Hemagglutinin., и . Pacific Symposium on Biocomputing, стр. 492-503. (2009)Folding and misfolding of the collagen triple helix: Markov analysis of molecular dynamics simulations, , и . BIOPHYSICAL JOURNAL, 93 (12): 4108-4115 (декабря 2007)Meeting halfway on the bridge between protein folding theory and experiment. Proceedings of National Academy of Sciences, 100 (7): 3555--3556 (апреля 2003)How well can simulation predict protein folding kinetics and thermodynamics?, , , и . Annual Review Biophys. BioMol. Struct., (2005)Folding@Home and Genome@Home: Using distributed computing to tackle previously intractable problems in computational biology, , , и . (2002)Everything you wanted to know about Markov State Models but were afraid to ask, , и . Methods, 52 (1): 99--105 (2010)Using path sampling to build better Markovian state models: Predicting the folding rate and mechanism of a tryptophan zipper beta hairpin, , и . Journal of Chemical Physics, 121 (1): 415-425 (2004)