T-WPPDC is a minimally parameterized algorithm for both pattern discovery and sequence classification that directly incorporates positional information.
Hetero-RP (Heterogeneity Rescaling Pursuit) is a scalable and tuning-free preprocessing framework, which weighs important features more highly than less important ones in accord with implicitly existing auxiliary knowledge.
EukRep is a k-mer-based strategy, for eukaryotic sequence identification and applied it to environmental samples to show that it enables genome recovery, genome completeness evaluation, and prediction of metabolic potential.
miRClassify is a novel machine learning-based web server which can rapidly identify miRNA from the primary sequence and classify it into a miRNA family in regardless of similarity in sequence and structure.
CARROT is a tool for relationship inference that leverages linkage disequilibrium to differentiate between rotated relationships, such as (first-, second-, etc) uncle-niece.
CancerIN is a web server developed for predicting anticancer activity of molecules. Similarity based approach has been used for discrimination or classification of anticancer and non-anticancer molecule.
R-SVM is a SVM-based method for doing supervised pattern recognition(classification) with microarray gene expression data. The method uses SVM for both classification and for selecting a subset of relevant genes according to their relative contribution in the classification. This process is done recursively so that a series of gene subsets and classification models can be obtained in a recursive manner, at different levels of gene selection. The performance of the classification can be evaluated either on an independent test data set or by cross validation on the same data set. R-SVM also includes an option for permutation experiments to assess the significance of the performance.