This article is part of the supplement: Bioinformatics Methods for Biomedical Complex System Applications .

Research

Protopia: a protein-protein interaction tool

Alejandro Real-Chicharro¹ , Iván Ruiz-Mostazo² , Ismael Navas-Delgado² , Amine Kerzazi² , Othmane Chniber² , Francisca Sánchez-Jiménez¹ , Miguel Ángel Medina¹ and José F Aldana-Montes²

¹  University of Malaga and "CIBER de Enfermedades Raras, Instituto de Salud Carlos III" (unit 741), Department of Molecular Biology and Biochemistry. Faculty of Sciences, Spain

²  University of Malaga, Computer Languages and Computing Science Department, Spain

author email corresponding author email

BMC Bioinformatics 2009, 10(Suppl 12):S17doi:10.1186/1471-2105-10-S12-S17

Published:	15 October 2009

Abstract

Background

Protein-protein interactions can be considered the basic skeleton for living organism self-organization and homeostasis. Impressive quantities of experimental data are being obtained and computational tools are essential to integrate and to organize this information. This paper presents Protopia, a biological tool that offers a way of searching for proteins and their interactions in different Protein Interaction Web Databases, as a part of a multidisciplinary initiative of our institution for the integration of biological data http://asp.uma.es webcite.

Results

The tool accesses the different Databases (at present, the free version of Transfac, DIP, Hprd, Int-Act and iHop), and results are expressed with biological protein names or databases codes and can be depicted as a vector or a matrix. They can be represented and handled interactively as an organic graph. Comparison among databases is carried out using the Uniprot codes annotated for each protein.

Conclusion

The tool locates and integrates the current information stored in the aforementioned databases, and redundancies among them are detected. Results are compatible with the most important network analysers, so that they can be compared and analysed by other world-wide known tools and platforms. The visualization possibilities help to attain this goal and they are especially interesting for handling multiple-step or complex networks.