We are interested in the design of methods for gaining biological knowledge from the analysis of high-throughput data, mainly from genomics, transcriptomics, and molecular markers. The philosophy of the group is that biological discovery is preceded by, or at least run in parallel to, the design of proper methods of data analysis. This is particularly true now that biology is flooded with quantitative data arising from the new sequencing technologies, microarrays, and other high-throughput technologies. We have worked on methods for the estimation of quantitative trait loci (QTLs) and the estimation of genetic diversity using molecular markers; automatic pipelines for processing and analyzing ESTs and, more recently, RNA-Seq data; algorithms for the assembling and annotation of genomes; and the application of Shannon’s information theory to estimate transcriptome and gene properties.