PSP server contains a collection of web services that address several protein structure prediction (PSP) sub-problems. Each of these sub-problems focuses on a single structural feature of a protein and the PSP server is using a Learning Classifier System to predict them for a given sequence of amino acids.
ProSAT toolkit is a set of programs that allow building SVM based models for annotating amino acid residues in protein sequences using user supplied features (like PSI-BLAST profiles, or PSIPred profiles). In particular, the toolkit builds features using a window around the residue, and is equipped with a specialized kernel function (normalized second order exponential kernel function nsoe ) along with the standard svm kernel function.
svmPRAT is a general purpose protein residue annotation toolkit to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates annotation problem as a classification or regression problem using support vector machines. The key features of svmPRAT are its ease of use to incorporate any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that allows better capture of signals for certain prediction problems.
Coevolution , an integrated online system that enables comparative analyses of residue coevolution with a comprehensive set of commonly used scoring functions, including Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Variation (ELSC), mutual information and correlation-based methods.