Subject
We are interested in using knowledge about the interwoven relationships occurrying at the microscopic scale to understand behaviors that unfold at a spatiotemporally larger scale, associated with the emergence of complex phenotypes or high-level biological functionality.
Under this approach we advance in three lines of research: the study of adult neurogenesis processes from single cell transcriptional landscapes, the analysis of splicing regulation processes and the problem of drug repositioning.  
What are the active gene regulatory networks that sustain a given cell type or developmental stage? What patterns are hidden in the nucleotide sequences of splicing sites to ensure the fidelity of immature transcript processing? Is it possible to recommend new therapeutic targets for known approved drugs? These are some questions we are interested in answering.

Approach
To carry out our projects we use huge amounts of data available in public repositories as well as our own data generated by our collaborators. To transform all this data into biologically relevant information and produce testable hypotheses, we use data-mining and heterogeneous data integration techniques, dimensionality reduction methodologies and complex network theory.

Advances
In recent works we have implemented novel drug repositioning systems for the TDR-targets project (tdrtargets.org) which is a resource open to the community to facilitate the research of new treatments for neglected tropical diseases.
We have also advanced in the study of splicing site recognition and splicing regulation processes and developed bioinformatics tools for the study of these processes through RNAseq experiments (the most widely used technique at present).
Finally, we developed a method to identify biologically relevant cell communities in single cell transcriptional landscapes.