Complex networks equipped with topological data analysis are one of the promising tools in the study of biological systems (e.g. evolution dynamics, brain correlation, breast cancer diagnosis, etc. . . ). jHoles implements the clique weight rank persistent homology algorithm. jHoles, a new version of Holes, is an algorithm based on persistent homology for studying the connectivity features of complex networks. jHoles fills the lack of an efficient implementation of the filtering process for clique weight rank homology. 

jHoles has been developed by the collaboration among Matteo Rucco, Giovanni Petri, Jacopo Binchi, Francesco Vaccarino and Emanuela Merelli from University of Camerino and ISI Foundation.

jHoles is supported by the financial support of the Future and Emerging Technologies (FET) programme within within the Seventh Framework Programme (FP7) for Research of the European Commission, under the FP7 FET-Proactive Call 8 - DyMCS, Grant Agreement TOPDRIM, number FP7-ICT-318121.

Example of topological graph obtained from antibodies' network. The nodes are simplices involved in persistent topological holes. An edge exists between two nodes if they belong to the same hole. The thickness of the edge is proportional to the frequency of appearance.

A Java High Performance Tool For Topological Data Analysis