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dc.contributor.authorAzginoglu, Nuh
dc.contributor.authorAydin, Zafer
dc.contributor.authorCelik, Mete
dc.date.accessioned2021-02-16T08:50:10Z
dc.date.available2021-02-16T08:50:10Z
dc.date.issued01.01.2020en_US
dc.identifier.issn1757-6334
dc.identifier.issn0219-7200
dc.identifier.otherPubMed ID: 32649260
dc.identifier.urihttps://doi.org/10.1142/S0219720020500225
dc.identifier.urihttps://hdl.handle.net/20.500.12573/561
dc.descriptionThe experiments calculations reported in this paper were partially performed at TUBITAK ULAKBIM, High Performance and Grid Computing Center (TRUBA resources). This work was supported by 3501 TUBITAK National Young Researchers Career Award [Grant Number 113E550].en_US
dc.description.abstractPredicting structural properties of proteins plays a key role in predicting the 3D structure of proteins. In this study, new structural profile matrices (SPM) are developed for protein secondary structure, solvent accessibility and torsion angle class predictions, which could be used as input to 3D prediction algorithms. The structural templates employed in computing SPMs are detected by eight alignment methods in LOMETS server, gap affine alignment method, ScanProsite, PfamScan, and HHblits. The contribution of each template is weighted by its similarity to target, which is assessed by several sequence alignment scores. For comparison, the SPMs are also computed using Homolpro, which uses BLAST for target template alignments and does not assign weights to templates. Incorporating the SPMs into DSPRED classifier, the prediction accuracy improves significantly as demonstrated by cross-validation experiments on two difficult benchmarks. The most accurate predictions are obtained using the SPMs derived by threading methods in LOMETS server. On the other hand, the computational cost of computing these SPMs was the highest.en_US
dc.description.sponsorshipTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) 3501 113E550en_US
dc.language.isoengen_US
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD, 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPOREen_US
dc.relation.isversionof10.1142/S0219720020500225en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectstructural profile matrixen_US
dc.subjecttorsion angleen_US
dc.subjectsolvent accessibilityen_US
dc.subjectsecondary structureen_US
dc.subjectProtein structure predictionen_US
dc.titleStructural profile matrices for predicting structural properties of proteinsen_US
dc.typearticleen_US
dc.contributor.departmentAGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.contributor.authorID0000-0002-4074-7366en_US
dc.identifier.volumeVolume: 18en_US
dc.identifier.issue4en_US
dc.relation.journalJOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGYen_US
dc.relation.tubitak113E550
dc.relation.tubitak3501
dc.relation.publicationcategoryMakale - Uluslararası - Editör Denetimli Dergien_US


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