INstruct is a database of 3D protein Interactome networks with structural resolution. It currently catalogues 6,587 human, 644 A. thaliana, 120 C. elegans, 166 D. melanogaster, 119 M. musculus, 1273 S. cerevisiae, and 37 S. pombe structurally resolved interactions. The interactions shown on this site have been curated from some of the most popular interaction databases and filtered to reflect only binary interactions that meet our strict quality criteria described by Wang, X. et al. (2012). The schematic below shows how we are then able to reconstruct 3D interaction interfaces for our high-quality set by using available co-crystal structures. [paper]


HINT (High-quality interactomes) is a database of high-quality protein-protein interactions in different organisms. These have been compiled from different sources and then filtered both systematically and manually to remove erroneous and low-quality interactions. There are 27,356 binary and 7,629 co-complex interactions for human, 11,936 binary and 16,294 co-complex interactions for S. cerevisiae, 160 binary and 417 co-complex interactions for S. pombe, and 211 binary interactions for O. sativa. HINT can be used for individual queries as well as for batch downloads. [paper]



mutation3D is a functional prediction and visualization tool for studying the spatial arrangement of amino acid substitutions on protein models and structures. It can be used to identify clusters of amino acid substitutions arising from somatic cancer mutations across many patients in order to identify functional hotspots and fuel downstream hypotheses. It is also useful for clustering other kinds of mutational data, or simply as a tool to quickly assess relative locations of amino acids in proteins.

[In Press]


BISQUE (The Biological Sequence Exchange) is a web server and customizable command-line tool for converting molecular identifiers and their contained loci and variants between different database conventions. BISQUE uses a graph traversal algorithm to generalize the conversion process for residues in the human genome, genes, transcripts, and proteins, allowing for conversion across classes of molecules and in all directions through an intuitive web interface and a URL-based web service.

[In Press]


ClusterONE (Clustering with Overlapping Neighborhood Expansion) is a graph clustering algorithm that is able to handle weighted graphs and readily generates overlapping clusters. Owing to these properties, it is especially useful for detecting protein complexes in protein-protein interaction networks with associated confidence values. ClusterONE is available as a standalone command-line application, or as a plugin to Cytoscape or ProCope.

ClusterONE is maintained by collaborators at the Paccanaro Lab. [paper]