title: Applying undertaker cost functions to model quality assessment.
abstract: Undertaker is a program designed to help predict protein structure using alignments to proteins of known structure and fragment assembly. The program generates conformations and uses cost functions to select the best structures from among the generated conformations. This paper describes the use of Undertaker's cost functions for model quality assessment. We achieve an accuracy that is similar to other methods, without using consensus-based techniques. Adding consensus-based features further improves our approach substantially. We report several correlation measures, including a new weighted version of Kendall's tau (tau(3)) and show model quality assessment results superior to previously published results on all correlation measures when using only models with no missing atoms.
authors.affiliation: University of California at Santa Cruz, Biomolecular Engineering, Santa Cruz, CA, USA.
authors.forename: John
authors.initials: J
authors.lastname: Archie
authors.forename: Kevin
authors.initials: K
authors.lastname: Karplus
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results
chemical_list: D011506:Proteins