Handle URI:
http://hdl.handle.net/10754/598583
Title:
Improving decoy databases for protein folding algorithms
Authors:
Lindsey, Aaron; Yeh, Hsin-Yi (Cindy); Wu, Chih-Peng; Thomas, Shawna; Amato, Nancy M.
Abstract:
Copyright © 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.
Citation:
Lindsey 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.
Publisher:
Association for Computing Machinery (ACM)
Journal:
Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
2014
DOI:
10.1145/2649387.2660839
Type:
Conference Paper
Sponsors:
This 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).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorLindsey, Aaronen
dc.contributor.authorYeh, Hsin-Yi (Cindy)en
dc.contributor.authorWu, Chih-Pengen
dc.contributor.authorThomas, Shawnaen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-25T13:32:34Zen
dc.date.available2016-02-25T13:32:34Zen
dc.date.issued2014en
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.en
dc.identifier.doi10.1145/2649387.2660839en
dc.identifier.urihttp://hdl.handle.net/10754/598583en
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.en
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).en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.subjectDecoy databasesen
dc.subjectProtein foldingen
dc.subjectSampling methodsen
dc.titleImproving decoy databases for protein folding algorithmsen
dc.typeConference Paperen
dc.identifier.journalProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14en
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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