Research Interests

I am a Miguel Servet researcher at the Integrative Biomedical Informatics Group, which belongs to the Research Unit on Biomedical Informatics (GRIB).

My research is focused in developing bioinformatic approaches that help us understanding the mechanisms underlying human diseases. I am  also interested in understanding the mechanisms by which drugs produce undesired side effects. In this regard, I am interested in identifying the functional modules that, when disrupted, lead to disease phenotypes. 

Nowadays,  a lot of biomedical information can be found in publicly available resources such as publication or databases over the web, but often this information is fragmented and scattered over many different repositories. Thus, an important aspect of my research is to identify, extract, integrate and make use of these information sources in a meaningful way to answer different questions.

One example is DisGeNET, a comprehensive database on the genetic basis of human diseases (DisGeNET), that covers mendelian, complex and environmental diseases. The database can be represented as a graph, and emergent properties of gene-disease association can be studied by applying graph analysis methods. In addition, by studying the functional annotation of the disease genes, we can learn more about the biological mechanisms underlying human genetic diseases. More details can be found here. Finally, we have made the DisGeNET database available through a Cytoscape plugin.

I am also interested in studying in more detail the effect of perturbations on the dynamics of the biological processes that are related to disease phenotypes. The perturbations can be genetic (such as a mutation in a gene that affects protein function) or environmental (such as a drug or a toxin). In this regard, we are working in an approach to integrate information on the effect of such perturbations in biological network models, and to simulate the effect of the perturbations in the dynamic of the system. More details can be found here.

More generally, I am also working towards developing approaches and tools that helps to bridge the gap between the development and curation of static models of biological processes (such as metabolic and signal transduction pathways, or gene regulatory networks) and their use for building dynamical models of these processes. See this publication for more information about these ideas.

Finally, I am also interested in developing and applying text mining approaches for the extraction of relationships between biomedical entities from the biomedical literature. In the past years we have developed NER systems for the identification of mentions of gene sequence variants from MEDLINE abstracts, and linkage of the mentions found in text to the corresponding database identifiers (in this case dbSNP). In addition, we have developed a corpus with annotations for variation mentions for the evaluation of this kind of NER systems. Currently, we are working on the application of Natural Language Processing approaches for the identification and extraction of different types of relationships between biomedical entities from text.