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dc.contributor.authorLindsey, Aaron
dc.contributor.authorYeh, Hsin-Yi (Cindy)
dc.contributor.authorWu, Chih-Peng
dc.contributor.authorThomas, Shawna
dc.contributor.authorAmato, Nancy M.
dc.date.accessioned2016-02-25T13:32:34Z
dc.date.available2016-02-25T13:32:34Z
dc.date.issued2014
dc.identifier.citationLindsey A, Yeh H-Y (Cindy), Wu C-P, Thomas S, Amato NM (2014) Improving decoy databases for protein folding algorithms. Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB ’14. Available: http://dx.doi.org/10.1145/2649387.2660839.
dc.identifier.doi10.1145/2649387.2660839
dc.identifier.urihttp://hdl.handle.net/10754/598583
dc.description.abstractCopyright © 2014 ACM. Predicting protein structures and simulating protein folding are two of the most important problems in computational biology today. Simulation methods rely on a scoring function to distinguish the native structure (the most energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing redundant structures. We test our approach on 17 different decoy databases of varying size and type and show significant improvement across a variety of metrics. We also test our improved databases on a popular modern scoring function and show that they contain a greater number of native-like structures than the original databases, thereby producing a more rigorous database for testing scoring functions.
dc.description.sponsorshipThis work is supported in part by NSF awards CRI-0551685,CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266 by THECBNHARP award 000512-0097-2009, by Chevron, IBM, Intel,Oracle/Sun and by Award KUS-C1-016-04, made by KingAbdullah University of Science and Technology (KAUST).
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectDecoy databases
dc.subjectProtein folding
dc.subjectSampling methods
dc.titleImproving decoy databases for protein folding algorithms
dc.typeConference Paper
dc.identifier.journalProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14
dc.contributor.institutionTexas A and M University, College Station, United States
kaust.grant.numberKUS-C1-016-04


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