The Genomics of Gene Expression Lab of the the Bioinformatics Department at the Centro de Investigación Príncipe Felipe develops statistical and bioinformatics tools for the analysis and understanding of genome-wide gene expression data. The Genomics of Gene Expression Lad is lead by Ana Victoria Conesa Cegarra.She leads the Genomics of Gene Expression Lab at the Computational Genomics Program of
the Centro de Investigación Príncipe Felipe, Valencia (Spain). For that she has developed statistical methods and software tools that analyze the (dynamics aspects of) transcriptome data, integrate these with other types of molecular data and annotate them functionally. She has applied these methods to gene expression characterization in both biomedical and model organism settings, as in non-model species -specially plants-, for which I have extensively collaborated with scientists in Europe, USA, South Africa and South America. Her current research uses NGS technologies to investigate the functional implications of gene expression and regulation. She is developer of popular software tools such as Blast2GO (functional annotation of novel sequence data), Paintomics (visualization of integrated pathway data) and Qualimap (quality control of mapped NGS data), and have published statistical tools for gene expression analysis such as maSigPro (time series analysis), minAS (multivariate feature selection), ASCA-genes (multivariate multifactorial gene expression analysis), SEA (user-friendly software and functional analysis of time course gene expression data) and NOIseq (RNA-seq differential expression analysis). At present she is leading several research projects where high-throughput sequencing is used to analyze gene expression. One of such projects is STATegra, a FP7 funded project where she is coordinator. STATegra will develop statistical tools for the integration of diverse NGS, proteomics and metabolomics data. Other projects involve the functional characterization of non-long coding RNAs, and the integration of RNA-seq, Methyl-seq and DNA-seq for studying disease and adaptation processes. Next to my research, I have an intensive activity in bioinformatics education and training and I have also been involved in the formation two spin-off companies in the area of biotechnology and bioinformatics.
