‘Bioinformatic algorithms of new generation for analysing gene expression data’

Alvaro Mateos Gil, Francesco Falciani. Javier Santoyo, Joaquín Dopazo, Ramón Díaz Uriarte.

This research group has been working intensely during recent years in the field of functional genomics, with results that include publications and the development of the GEPAS platform, an integrated web-based suite of programs for microarray data analysis. The main objective of this project implies the development of a new generation of algorithms for expanding the possibilities of analyzing microarray data by using new statistical methods and integrating information, as well as expanding the study of gene interaction to heterogeneous systems. Most of the algorithms and tools developed in the project can be implemented as new functionalities of the GEPAS package. The specific objectives of this project are: i) Development of new multivariate methods for recovering genes differentially expressed between conditions. ii) The search for efficient predictors. iii) Development of algorithms that include information as part of the process of gene selection and/or definition of molecular signatures: an aspect of much interest is data mining. The concept of %22guilt by association%22 will be the annotation paradigm in functional genomics experiments. iv) The study of interactions not only within, but also between systems will help us to understand biological processes that occur at tissue level.