Search Results - "Singhal, Nina"

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  1. 1

    Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics by Chodera, John D, Singhal, Nina, Pande, Vijay S, Dill, Ken A, Swope, William C

    Published in The Journal of chemical physics (21-04-2007)
    “…To meet the challenge of modeling the conformational dynamics of biological macromolecules over long time scales, much recent effort has been devoted to…”
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    Journal Article
  2. 2

    Using path sampling to build better Markovian state models: predicting the folding rate and mechanism of a tryptophan zipper beta hairpin by Singhal, Nina, Snow, Christopher D, Pande, Vijay S

    Published in The Journal of chemical physics (01-07-2004)
    “…We propose an efficient method for the prediction of protein folding rate constants and mechanisms. We use molecular dynamics simulation data to build…”
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    Journal Article
  3. 3

    Ensemble Molecular Dynamics Yields Submillisecond Kinetics and Intermediates of Membrane Fusion by Kasson, Peter M., Kelley, Nicholas W., Singhal, Nina, Vrljic, Marija, Brunger, Axel T., Pande, Vijay S.

    “…Lipid membrane fusion is critical to cellular transport and signaling processes such as constitutive secretion, neurotransmitter release, and infection by…”
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    Journal Article
  4. 4

    Calculation of the distribution of eigenvalues and eigenvectors in Markovian state models for molecular dynamics by Hinrichs, Nina Singhal, Pande, Vijay S

    Published in The Journal of chemical physics (28-06-2007)
    “…Markovian state models (MSMs) are a convenient and efficient means to compactly describe the kinetics of a molecular system as well as a formalism for using…”
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    Journal Article
  5. 5

    Error analysis and efficient sampling in Markovian state models for molecular dynamics by Singhal, Nina, Pande, Vijay S

    Published in The Journal of chemical physics (22-11-2005)
    “…In previous work, we described a Markovian state model (MSM) for analyzing molecular-dynamics trajectories, which involved grouping conformations into states…”
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    Journal Article
  6. 6

    Persistent voids: a new structural metric for membrane fusion by Kasson, Peter M., Zomorodian, Afra, Park, Sanghyun, Singhal, Nina, Guibas, Leonidas J., Pande, Vijay S.

    Published in Bioinformatics (15-07-2007)
    “…Motivation: Membrane fusion constitutes a key stage in cellular processes such as synaptic neurotransmission and infection by enveloped viruses. Current…”
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    Journal Article
  7. 7
  8. 8

    Algorithms for building models of molecular motion from simulations by Hinrichs, Nina Singhal

    Published 01-01-2007
    “…Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical…”
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    Dissertation
  9. 9

    Algorithms for building models of molecular motion from simulations by Hinrichs, Nina Singhal

    “…Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical…”
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    Dissertation
  10. 10

    Bayesian hidden Markov model analysis of single-molecule force spectroscopy: Characterizing kinetics under measurement uncertainty by Chodera, John D, Elms, Phillip, Noé, Frank, Keller, Bettina, Kaiser, Christian M, Ewall-Wice, Aaron, Marqusee, Susan, Bustamante, Carlos, Hinrichs, Nina Singhal

    Published 05-08-2011
    “…Single-molecule force spectroscopy has proven to be a powerful tool for studying the kinetic behavior of biomolecules. Through application of an external…”
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    Journal Article