Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

Drawert, Brian; Hellander, Andreas; Bales, Ben; Banerjee, Debjani; Bellesia, Giovanni; Daigle, Bernie J.; Douglas, Geoffrey; Gu, Mengyuan; Gupta, Anand; Hellander, Stefan; Horuk, Chris; Nath, Dibyendu; Takkar, Aviral; Wu, Sheng; Lötstedt, Per; Krintz, Chandra; Petzold, Linda R.

doi:10.1371/journal.pcbi.1005220

Title: Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

Journal Article · Thu Dec 08 00:00:00 EST 2016 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1005220· OSTI ID:1423939

^[1]; Hellander, Andreas ^[2]; Bales, Ben ^[3]; Banerjee, Debjani ^[1]; Bellesia, Giovanni ^[1]; Daigle, Bernie J. ^[4]; Douglas, Geoffrey ^[1]; Gu, Mengyuan ^[1]; Gupta, Anand ^[1]; Hellander, Stefan ^[1]; Horuk, Chris ^[1]; Nath, Dibyendu ^[1]; Takkar, Aviral ^[1];

^[1]; Lötstedt, Per ^[2];

^[1]; Petzold, Linda R. ^[5]

Univ. of California Santa Barbara, Santa Barbara, CA (United States). Dept. of Computer Science
Uppsala Univ. (Sweden). Dept. of Information Technology, Division of Scientific Computing
Univ. of California Santa Barbara, Santa Barbara, CA (United States). Dept. of Mechanical Engineering
Univ. of Memphis, Memphis, TN (United States). Dept. of Biological Sciences and Computer Science
Univ. of California Santa Barbara, Santa Barbara, CA (United States). Dept. of Computer Science and Dept. of Mechanical Engineering

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

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Research Organization:: Univ. of California Santa Barbara, Santa Barbara, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division; National Institutes of Health (NIH); Institute for Collaborative Biotechnologies (ICB); US Army Research Office (ARO); National Science Foundation (NSF); eSSENCE Swedish strategic initiative on eScience

Grant/Contract Number:: SC0008975; R01-EB014877; R01-GM113241; W911NF-09-0001; DMS-1001012

OSTI ID:: 1423939

Journal Information:: PLoS Computational Biology (Online), Vol. 12, Issue 12; ISSN 1553-7358

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 34 works

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