Professional interests and goals: Unlike other organisms, plants spend their whole life in the same place. That makes them specialists in the census, integration, and dynamic response to environmental cues. Transcription factors (TFs) are key players in the communication between these layers, “working” at the link between signal sensing and control of the cellular responses at the gene expression level. The importance of a TF underlies on its ability to recognize specific DNA sequences to coordinate the activation or repression of particular genes (So-called target genes). A vast brochure of experimental approaches including microarray, RNA-seq, ChIP-seq, DAP-seq, SELEX-Seq, among others, has endowed the scientific community with high-throughput tools to unravel an unprecedented, genome-wide, number of functional links between TFs and their target genes. It is here where my three main interests/questions reside: 1) How can we integrate the massive amount of experimental data available on model plants (as Arabidopsis thaliana), to produce specific hypotheses on the control of plant biological processes (such as the accumulation of the metabolite). 2) Do we need all of these different types of data to generate robust gene-regulatory hypotheses? For instance, could we predict a ChIP-seq using experiments less laborious as RNA-seq? 3) Could we build statistical models that allow us to transfer our current gene regulatory knowledge from model plants to non-model plants? Having said that, my short-term (as a graduate student) and long-term (as Postdoc and PI hopefully) goals are contributing to solving these questions using/developing computational tools.
General interests: I enjoy spending my free time with my family, travelling, and trying new food as much as possible!