skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Adaptive ensemble simulations of biomolecules

Abstract

Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling highlevel algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. In conclusion, we describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.

Authors:
 [1];  [2]
  1. Univ. of Virginia, Charlottesville, VA (United States); Uppsala Univ., Uppsala (Sweden)
  2. Rutgers Univ., Piscataway, NJ (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)
OSTI Identifier:
1491694
Report Number(s):
BNL-210893-2019-JAAM
Journal ID: ISSN 0959-440X
Grant/Contract Number:  
SC0012704
Resource Type:
Accepted Manuscript
Journal Name:
Current Opinion in Structural Biology
Additional Journal Information:
Journal Volume: 52; Journal Issue: C; Journal ID: ISSN 0959-440X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; biomolecules

Citation Formats

Kasson, Peter M., and Jha, Shantenu. Adaptive ensemble simulations of biomolecules. United States: N. p., 2018. Web. doi:10.1016/j.sbi.2018.09.005.
Kasson, Peter M., & Jha, Shantenu. Adaptive ensemble simulations of biomolecules. United States. doi:10.1016/j.sbi.2018.09.005.
Kasson, Peter M., and Jha, Shantenu. Tue . "Adaptive ensemble simulations of biomolecules". United States. doi:10.1016/j.sbi.2018.09.005. https://www.osti.gov/servlets/purl/1491694.
@article{osti_1491694,
title = {Adaptive ensemble simulations of biomolecules},
author = {Kasson, Peter M. and Jha, Shantenu},
abstractNote = {Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling highlevel algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. In conclusion, we describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.},
doi = {10.1016/j.sbi.2018.09.005},
journal = {Current Opinion in Structural Biology},
number = C,
volume = 52,
place = {United States},
year = {2018},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 1 work
Citation information provided by
Web of Science

Save / Share: