Integration Methods for Biological Data Sources

Nowadays, recent technologies in biology has gained a lot of attention, because of the massive data they produced with different types, very complex structures and various interaction categories. They allowed to perform deep analysis on cell structure and it’s sub-system. Moreover, They enabled construction of complex networks that represent the extracted data and the mutual interactions between biological entities of diverse types. However, most of users, especially researchers and biologists, find it difficult to do their experiments on a set of data of various types stored in multiple databases. In this paper, we present the state of the art for data integration based on collective mining, using various types of networked biological data. Moreover, we propose a new approach to make it possible to integrate heterogeneous data in the MicroCancer platform, recently developed by our laboratory, to deal with micro-array data.