Scoring functions for protein structure prediction

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dc.catalogadoraba
dc.contributor.authorMelo Ledermann, Francisco Javier
dc.contributor.authorFeytmans, E.
dc.contributor.editorSchwede, Torsten
dc.contributor.editorPeitsch, Manuel
dc.date.accessioned2025-02-06T20:11:48Z
dc.date.available2025-02-06T20:11:48Z
dc.date.issued2008
dc.description.abstractThe following sections are included: Introduction Structure and Components of Scoring Functions Contact Scoring Functions Distance-dependent Scoring Functions Accessible Surface Scoring Functions Combined Scoring Functions How is a Scoring Function Derived? Selection of Source Experimental Data Reference Systems How is a Scoring Function Used? Classical Overall Score Calculation Sequence space reference frame Structure space reference frame Classical Detailed Score Calculation Variations on Score Calculations Typical Applications of Scoring Functions in Protein Structure Prediction Fold Assessment Model Ranking Error Detection Folding and Molecular Simulations Other Applications of Scoring Functions Future Outlook Reference Systems and Atom Type Definitions Solvation Models Evolutionary Information Multivariate Scoring Functions Acknowledgements References
dc.format.extent27 páginas
dc.fuente.origenSIPA
dc.identifier.doi10.1142/9789812778789_0003
dc.identifier.eisbn978-981-4472-41-8
dc.identifier.eissn1097-0134
dc.identifier.isbn978-981-277-877-2
dc.identifier.issn0887-3585
dc.identifier.urihttps://doi.org/10.1142/9789812778789_0003
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/102201
dc.identifier.wosidWOS:000246894800008
dc.information.autorucFacultad de Ciencias Biológicas; Melo Ledermann, Francisco Javier; 0000-0002-0424-5991; 82342
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final75
dc.pagina.inicio67
dc.relation.ispartofComputational Structural Biology, London : World Scientific Publishing, 2008.
dc.rightsacceso restringido
dc.subject.ddc570
dc.subject.deweyBiologíaes_ES
dc.titleScoring functions for protein structure prediction
dc.typecapítulo de libro
sipa.codpersvinculados82342
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