EGAN (Exploratory Gene Association Networks) is a software tool that allows a domain expert (a biologist) to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of entities (genes), relationships (protein-protein interactions, literature co-occurence, etc.) and meta-data (annotation, signaling pathways, etc.).

Python can be used to solve several problems that research laboratories face almost everyday. Data manipulation, biological data retrieval and parsing, automation, and simulation of biological problems are some of the tasks that can be performed in an effective way with computers and a suitable programming language.

Bioinformatics, the use of computer technology to manage biological information, made its spectacular debut a few years ago, as the first trickles of gene sequence information from the Human Genome Program (HGP) and other sequencing projects grew into a deluge. Individuals with the skills to work on the interface between molecular biology and computer science instantly became some of the most sought-after job applicants in the biopharma world. With about 3 billion base pairs on its agenda, and a target completion date of 2005, HGP alone should foster a continuing explosion of data and a robust job market for computational biologists.

Bioinformatics provides the computational support for functional genomics which will link the behavior of cells, organism amd population to the information encoded in the genomes, as well as structural genomics. The utility of bioinformatics lies in the identification of useful genes leading to the development of new gene products. The subject covers topics such as protein modeling and sequence alignment, expression data analysis, and comparartive genomics. It combines algorithmic, statistical and database methods for studying biological problems also.