Prediction of protein secondary structure by mining structural fragment database

dc.contributor.author Cheng, Haitao
dc.contributor.author Jernigan, Robert
dc.contributor.author Sen, Taner
dc.contributor.author Kloczkowski, Andrzej
dc.contributor.author Margaritis, Dimitris
dc.contributor.author Jernigan, Robert
dc.contributor.department Biochemistry, Biophysics and Molecular Biology
dc.contributor.department Computer Science
dc.contributor.department Computer Science
dc.date 2018-02-19T04:20:36.000
dc.date.accessioned 2020-06-29T23:46:10Z
dc.date.available 2020-06-29T23:46:10Z
dc.date.copyright Sat Jan 01 00:00:00 UTC 2005
dc.date.issued 2005-05-26
dc.description.abstract <p>A new method for predicting protein secondary structure from amino acid sequence has been developed. The method is based on multiple sequence alignment of the query sequence with all other sequences with known structure from the protein data bank (PDB) by using BLAST. The fragments of the alignments belonging to proteins from the PBD are then used for further analysis. We have studied various schemes of assigning weights for matching segments and calculated normalized scores to predict one of the three secondary structures: α-helix, β-sheet, or coil. We applied several artificial intelligence techniques: decision trees (DT), neural networks (NN) and support vector machines (SVM) to improve the accuracy of predictions and found that SVM gave the best performance. Preliminary data show that combining the fragment mining approach with GOR V (Kloczkowski et al, Proteins 49 (2002) 154–166) for regions of low sequence similarity improves the prediction accuracy.</p>
dc.description.comments <p>This is a manuscript of an article published as Cheng, Haitao, Taner Z. Sen, Andrzej Kloczkowski, Dimitris Margaritis, and Robert L. Jernigan. "Prediction of protein secondary structure by mining structural fragment database." Polymer 46, no. 12 (2005): 4314-4321. doi: <a href="http://dx.doi.org/10.1016" target="_blank">10.1016/j.polymer.2005.02.040</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/bbmb_ag_pubs/171/
dc.identifier.articleid 1179
dc.identifier.contextkey 11160621
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath bbmb_ag_pubs/171
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/10634
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/bbmb_ag_pubs/171/2005_Jernigan_PredictionProtein.pdf|||Fri Jan 14 21:16:11 UTC 2022
dc.source.uri 10.1016/j.polymer.2005.02.040
dc.subject.disciplines Biochemistry, Biophysics, and Structural Biology
dc.subject.disciplines Bioinformatics
dc.subject.disciplines Computer Sciences
dc.subject.disciplines Molecular Biology
dc.subject.keywords Secondary structure
dc.subject.keywords Sequence
dc.subject.keywords Cut-off
dc.title Prediction of protein secondary structure by mining structural fragment database
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
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