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dc.contributor.authorWang, Tong
dc.contributor.authorYang, Yuedong
dc.contributor.authorZhou, Yaoqi
dc.contributor.authorGong, Haipeng
dc.date.accessioned2018-05-18T06:11:36Z
dc.date.available2018-05-18T06:11:36Z
dc.date.issued2017
dc.identifier.issn1367-4803
dc.identifier.doi10.1093/bioinformatics/btw668
dc.identifier.urihttp://hdl.handle.net/10072/124074
dc.description.abstractMotivation: The quality of fragment library determines the efficiency of fragment assembly, an approach that is widely used in most de novo protein-structure prediction algorithms. Conventional fragment libraries are constructed mainly based on the identities of amino acids, sometimes facilitated by predicted information including dihedral angles and secondary structures. However, it remains challenging to identify near-native fragment structures with low sequence homology. Results: We introduce a novel fragment-library-construction algorithm, LRFragLib, to improve the detection of near-native low-homology fragments of 7–10 residues, using a multi-stage, flexible selection protocol. Based on logistic regression scoring models, LRFragLib outperforms existing techniques by achieving a significantly higher precision and a comparable coverage on recent CASP protein sets in sampling near-native structures. The method also has a comparable computational efficiency to the fastest existing techniques with substantially reduced memory usage.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherOxford University Press
dc.relation.ispartofpagefrom1
dc.relation.ispartofpageto8
dc.relation.ispartofjournalBioinformatics
dc.subject.fieldofresearchMathematical sciences
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchBioinformatics and computational biology
dc.subject.fieldofresearchcode49
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode3102
dc.titleLRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.description.notepublicThis publication has been entered into Griffith Research Online as an Advanced Online Version.
gro.hasfulltextNo Full Text
gro.griffith.authorZhou, Yaoqi
gro.griffith.authorYang, Yuedong


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