Prediction of peptide bonding affinity: kernel methods for nonlinear modeling

Comparative Evaluation of Prediction Algorithms(COEPRA, http://www.coepra.org/) is a modeling competition organized to provide objective testing of various algorithms via the process of blind prediction for chemical, biological, and medical data. COEPRA's stated goals are to advance modeling algorithms and software as well as provide reference datasets to the research community. Transferable Atom Equivalent (TAE) RECON features are electron-density derived descriptors obtained by fragment reconstruction. MOE features are geometrical, structural, physiochemical and topological 2D descriptors.