Software resources created by members of the Clique Research Cluster
Software for fast dynamic community finding.
Software for scalable overlapping community finding on static graphs.
Tools for tracking and visualizing document and term clusters in dynamic text data.
An R package containing a suite of protein function prediction algorithms that exploits protein interaction data. Contains methods for importing interaction data and measuring predictive performance.
Python code for the imputation and prediction of quantitative genetic interactions.
Software tools for aggregating and exploring a diverse collection of matrix factorizations to produce a superior clustering, which takes the form of an overlapping hierarchy of clusters.
Java-based software implementing a data integration approach for performing multi-view clustering in domains where two or more related datasets are available.
C++ implementation of the Greedy Clique Expansion algorithm for detecting communities. The algorithm is especially designed for graphs in which most nodes belong to many communities. See this paper for more details.
Implementation of the successive group betweenness algorithm by Puzis et. al (2007): 'Fast algorithm for successive computation of group betweenness centrality'.
R package for performing Variational Bayesian inference for the Latent Position Cluster Model for network data. Includes model fit assessments, plotting functions, example datasets and a demo.
An R package for performing Bayesian Latent Class Analysis. Multiple methods are provided to fit mixtiure models to binary data, and plotting functions, model diagnostics and an example dataset are included.
Ancestry Mapper assigns genetic ancestry to an individual and studies relationships between local and global populations.