Aurora Torrente earned her PhD in Statistics from the Universidad Carlos III de Madrid (UC3M, Spain), where she currently works as a lecturer and a researcher. She has held postdoctoral positions at the Universidad Autónoma de Madrid (UAM, Spain) and the European Bioinformatics Institute (EBI, UK). Her research focuses on developing statistical tools for the study of gene expression data, which include techniques for pre-processing, managing, clustering and classifying large datasets of human transcriptomes from microarrays or oligonucleotide chips of high density. She has also carried out a large-scale analysis of gene expression data from a wide range of cell and cancer types to elucidate gene regulatory mechanisms that are shared by different tumors, based on appropriate linear models to describe the data. Currently, she is involved in a project focused on the analysis of massive RNA-seq data sets from cancer and normal cells. She has expert knowledge of statistical programming in R and Bioconductor for computational statistics (co-author of three packages), and is skilled in managing large data sets and in structuring their analysis in parallel in the platform LSF to overcome time or memory problems.