Predicting solvent accessibility: Higher accuracy using Bayesian statistics and optimized residue substitution classes
dc.contributor.author | Thompson, Michael J. | en_US |
dc.contributor.author | Goldstein, Richard A. | en_US |
dc.date.accessioned | 2006-04-28T17:02:28Z | |
dc.date.available | 2006-04-28T17:02:28Z | |
dc.date.issued | 1996-05 | en_US |
dc.identifier.citation | Thompson, Michael J.; Goldstein, Richard A. (1996)."Predicting solvent accessibility: Higher accuracy using Bayesian statistics and optimized residue substitution classes." Proteins: Structure, Function, and Genetics 25(1): 38-47. <http://hdl.handle.net/2027.42/38524> | en_US |
dc.identifier.issn | 0887-3585 | en_US |
dc.identifier.issn | 1097-0134 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/38524 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=8727318&dopt=citation | en_US |
dc.description.abstract | We introduce a novel Bayesian probabilistic method for predicting the solvent accessibilities of amino acid residues in globular proteins. Using single sequence data, this method achieves prediction accuracies higher than previously published methods. Substantially improved predictions—comparable to the highest accuracies reported in the literature to date—are obtained by representing alignments of the example proteins and their homologs as strings of residue substitution classes, depending on the side chain types observed at each alignment position. These results demonstrate the applicability of this relatively simple Bayesian approach to structure prediction and illustrate the utility of the classification methodology previously developed to extract information from aligned sets of structurally related proteins. © 1996 Wiley-Liss, Inc. | en_US |
dc.format.extent | 983641 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Chemistry | en_US |
dc.subject.other | Biochemistry and Biotechnology | en_US |
dc.title | Predicting solvent accessibility: Higher accuracy using Bayesian statistics and optimized residue substitution classes | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Biophysics Research Division, University of Michigan, Ann Arbor, Michigan 48109-1055 | en_US |
dc.contributor.affiliationum | Biophysics Research Division, University of Michigan, Ann Arbor, Michigan 48109-1055 ; Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055 ; Biophysics Research Division, Department of Chemistry, University of Michigan, Ann Arbor, MI 48109-1055. | en_US |
dc.identifier.pmid | 8727318 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/38524/1/4_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/prot.4 | en_US |
dc.identifier.source | Proteins: Structure, Function, and Genetics | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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