Theoretical enzyme design using the Kepler scientific workflows on the Grid

dc.contributor.authorWang, Jianwu
dc.contributor.authorKorambath, Prakashan
dc.contributor.authorKim, Seonah
dc.contributor.authorJohnson, Scott
dc.contributor.authorJin, Kejian
dc.contributor.authorCrawl, Daniel
dc.contributor.authorAltintas, Ilkay
dc.contributor.authorSmallen, Shava
dc.contributor.authorLabate, Bill
dc.contributor.authorHouk, Kendall N.
dc.date.accessioned2024-02-12T21:07:54Z
dc.date.available2024-02-12T21:07:54Z
dc.date.issued2010-06-01
dc.descriptionInternational Conference on Computational Science, ICCS 2010
dc.description.abstractOne of the greatest challenges in computational chemistry is the design of enzymes to catalyze non-natural chemical reactions. We focus on harnessing the distributed parallel computational power of the Grid to automate the inside-out process of enzyme design using scientific workflow systems. This paper presents a scientific workflow based approach to facilitate the inside-out enzyme design process in the Grid execution environment by providing features such as resource consolidation, task parallelism, provenance tracking, fault tolerance and workflow reuse, which results in an automated, pipelined, efficient, extensible, stable, and easy-to-use computational process for enzyme design.
dc.description.sponsorshipThe authors would like to thank the rest of the Kepler and UC Grid community for their collaboration. This work was supported by NSF SDCI Award OCI-0722079 for Kepler/CORE, NSF CEO:P Award No. DBI 0619060 for REAP, DOE SciDac Award No. DE-FC02-07ER25811 for SDM Center, and UCGRID Project. We also thank the support to the Houk group from NIH-NIGMS and DARPA.
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S1877050910001328
dc.format.extent10 pages
dc.genreconference papers and proceedings
dc.identifier.citationWang, Jianwu, Prakashan Korambath, Seonah Kim, Scott Johnson, Kejian Jin, Daniel Crawl, Ilkay Altintas, Shava Smallen, Bill Labate, and Kendall N. Houk. “Theoretical Enzyme Design Using the Kepler Scientific Workflows on the Grid.” Procedia Computer Science, ICCS 2010, 1, no. 1 (May 1, 2010): 1175–84. https://doi.org/10.1016/j.procs.2010.04.131.
dc.identifier.urihttps://doi.org/10.1016/j.procs.2010.04.131
dc.identifier.urihttp://hdl.handle.net/11603/31604
dc.language.isoen
dc.publisherElsevier
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.isformatofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Center for Accelerated Real Time Analysis
dc.relation.ispartofUMBC Data Science
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology (JCET)
dc.relation.ispartofUMBC Center for Real-time Distributed Sensing and Autonomy
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Information Systems Department Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0 DEED)en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectUMBC Big Data Analytics Lab
dc.titleTheoretical enzyme design using the Kepler scientific workflows on the Grid
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-9933-1170

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