A web-based protein interaction network visualizer

Salazar, Gustavo A; Meintjes, Ayton; Mazandu, Gaston K; Rapanoël, Holifidy A; Akinola, Richard O; Mulder, Nicola J

A web-based protein interaction network visualizer

Journal Article

2014-05-06

Journal Title

BMC Bioinformatics

Link to Journal

http://www.biomedcentral.com/1471-2105

Publisher

BioMed Central

Publisher

University of Cape Town

Department

Institute of Infectious Disease and Molecular Medicine

Faculty

Faculty of Health Sciences

License

http://creativecommons.org/licenses/by/4.0/

Abstract

Abstract Background Interaction between proteins is one of the most important mechanisms in the execution of cellular functions. The study of these interactions has provided insight into the functioning of an organism’s processes. As of October 2013, Homo sapiens had over 170000 Protein-Protein interactions (PPI) registered in the Interologous Interaction Database, which is only one of the many public resources where protein interactions can be accessed. These numbers exemplify the volume of data that research on the topic has generated. Visualization of large data sets is a well known strategy to make sense of information, and protein interaction data is no exception. There are several tools that allow the exploration of this data, providing different methods to visualize protein network interactions. However, there is still no native web tool that allows this data to be explored interactively online. Results Given the advances that web technologies have made recently it is time to bring these interactive views to the web to provide an easily accessible forum to visualize PPI. We have created a Web-based Protein Interaction Network Visualizer: PINV, an open source, native web application that facilitates the visualization of protein interactions ( http://biosual.cbio.uct.ac.za/pinv.html ). We developed PINV as a set of components that follow the protocol defined in BioJS and use the D3 library to create the graphic layouts. We demonstrate the use of PINV with multi-organism interaction networks for a predicted target from Mycobacterium tuberculosis, its interacting partners and its orthologs. Conclusions The resultant tool provides an attractive view of complex, fully interactive networks with components that allow the querying, filtering and manipulation of the visible subset. Moreover, as a web resource, PINV simplifies sharing and publishing, activities which are vital in today’s research collaborative environments. The source code is freely available for download at https://github.com/4ndr01d3/biosual .