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Showing 1–7 of 7 results
Advanced filters: Author: Pratyush Tiwary Clear advanced filters

  • As Nature Chemical Biology approaches its third decade we asked a collection of chemical biologists, “What do you think are the most exciting frontiers or the most needed developments in your main field of research?” — here is what they said.

    • Lona M. Alkhalaf
    • Cheryl Arrowsmith
    • Georg Winter
    Special Features
    Nature Chemical Biology
    Volume: 21, P: 6-15

  • Predictive machine learning models, while powerful, are often seen as black boxes. Here, the authors introduce a thermodynamics-inspired approach for generating rationale behind their explanations across diverse domains based on the proposed concept of interpretation entropy.

    • Shams Mehdi
    • Pratyush Tiwary
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-12

  • Adding prior experimentally or theoretically obtained knowledge to the training of recurrent neural networks may be challenging due to their feedback nature with arbitrarily long memories. The authors propose a path sampling approach that allows to include generic thermodynamic or kinetic constraints for learning of time series relevant to molecular dynamics and quantum systems.

    • Sun-Ting Tsai
    • Eric Fields
    • Pratyush Tiwary
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-10

  • Efficient sampling of rare events in all-atom molecular dynamics simulations remains a challenge. Here, the authors adapt the Predictive Information Bottleneck framework to sample biomolecular structure and dynamics through iterative rounds of biased simulations and deep learning.

    • Yihang Wang
    • João Marcelo Lamim Ribeiro
    • Pratyush Tiwary
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-8

  • Artificial neural networks have been successfully used for language recognition. Tsai et al. use the same techniques to link between language processing and prediction of molecular trajectories and show capability to predict complex thermodynamics and kinetics arising in chemical or biological physics.

    • Sun-Ting Tsai
    • En-Jui Kuo
    • Pratyush Tiwary
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-11

  • The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.

    • Massimiliano Bonomi
    • Giovanni Bussi
    • Andrew White
    Comments & Opinion
    Nature Methods
    Volume: 16, P: 670-673