Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling-Reference-Cited by-同舟云学术

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Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling

Published:2016-10-02 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
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Author:

Rasheed Muhibur¹,Clement Nathan¹,Bhowmick Abhishek¹,Bajaj Chandrajit¹

Affiliation:

1. Computer Science Dept., University of Texas at Austin, Austin, TX, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2975167.2975182

Reference46 articles.

1. Weighted sums of certain dependent random variables

2. An Efficient Higher-Order Fast Multipole Boundary Element Solution for Poisson–Boltzmann-Based Molecular Electrostatics

3. TexMol: interactive visual exploration of large flexible multi-component molecular complexes

4. NURBS based B-rep models for macromolecules and their properties

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bayesian Active Learning for Optimization and Uncertainty Quantification in Protein Docking;Journal of Chemical Theory and Computation;2020-06-19

2. A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness;Computer Methods in Applied Mechanics and Engineering;2019-06

3. Atomic Radius and Charge Parameter Uncertainty in Biomolecular Solvation Energy Calculations;Journal of Chemical Theory and Computation;2018-01-29

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