Poster: Context-sensitive use of bioinformatics tools with complementary functionalities for hypothesis generation

Bioinformatics tools can be of great help in mining and summarizing voluminous data. However, such tools are usually ineffective in dealing with heterogeneous data and have a limited array of functionalities. Integrated Bioinformatics tools with complementary functionalities (IBTCF) can potentially further knowledge discovery. In this paper, we have used a progressive IBTCF that infer complementary information from the literature, high throughput genomic data and the human curated Gene Ontology classification. Empirical analyses were performed to find an associations between Alzheimer´s disease and Tuberculosis, two seemingly disconnected diseases. The origin for this association is believed to be through matrix metalloproteinases (MMP) genes and their mode of action. The integrated system may also further multi-faceted issues in knowledge discovery.