This announcement solicits papers for a special track focusing on the understanding, and ultimately, the prediction, of protein structure.
Preferred papers should describe discovery, learning, or analysis approaches that lead to testable predictions. Predictive accuracy should be quantified and compared. Controls for homology and cross-validation should be stated explicitly. We encourage papers that exploit the large existing databases, including motif discovery, machine learning, probabilistic/statistical, empirical knowledge-based, and related methods.
Two broadly defined approaches to the understanding and prediction of protein structure are those based on energetics and those based on informatics. We are interested in strategies that embody either approach or that are hybrids between the two. This includes core domain and tertiary topology classification, analysis or prediction, amino acid packing and residue-residue contact studies, secondary structure or main chain torsion angle analysis, lattice folding models, synthetic or simulated energetics or potentials, predicting side-chain conformation, multiple-alignment or homology-derived techniques, distinguishing native from incorrectly folded models, amino acid environment matching, mutational analysis and the contribution of single amino acids, and statistical, machine learning or multi-strategy systems.
Full paper submission and publication is required for oral presentations. Each full paper will be reviewed by at least three independent referees.
Poster and demo sessions are available for researchers who wish to exhibit their work at PSB, but do not wish to prepare a paper.
Send papers and correspondence to:
A. Keith Dunker
Department of Biochemistry/Biophysics
Washington State University
Pullman, WA 99164-4660 USA
+1 (509) 335-5322
+1 (509) 335-9688 (fax)