We are interested in developing and applying computational tools for the study of functional effects for mutations in human genomes. One current focus is to develop reliable and efficient ways of analyzing synonymous mutations and indels (insertion/deletions). Another focus is to develop computational methods to predict the effects of mutations on protein-protein interactions and protein-nucleic acids interactions. To make our predictions we rely on a number of sequence-based features (including physicochemical features, predicted structural features, evolutionary information, and available functional annotations) and utilize a variety of computational methodologies (including machine learning methods). We are also actively developing bioinformatics databases and predictors.