Panagiotis Moulos holds a diploma in Applied Mathematics and Physics from the National Technical University of Athens (NTUA) and an MSc in Bioinformatics from the Free University of Brussels (ULB). He is currently a post-doctoral researcher in the Renal Fibrosis Lab, I2MC, Toulouse, France under the supervision of Dr. Joost Schanstra. Among others, his research interests include algorithms for the computational analysis and meta-analysis of high-throughput genomic data (DNA microarrays), relative software development and focus on statistical properties, statistical modeling and normalization of Next Generation Sequencing (NGS) data (ChIP-Seq, RNA-Seq). He is also interested in the application of Machine Learning techniques regarding the computational analysis of high-throughput genomic data with focus on dimensionality reduction and feature selection stability issues and recently developed interest on the analysis and meta-analysis of metabolomics MS data. Particular interest is given to the integration of lower level data representations (fundamental analysis of high-throughput genomic data) to higher level representations (over represented GO categories, mapping to metabolic pathways, building of transcriptional networks). Future goals include integration of NGS analytical methodologies to a common analysis workflow including data from other high-throughput genomic techniques (e.g. expression microarrays) and the setup of large scale mathematical models of specific metabolic pathways in order to approach functionalities in a systemic way. His practical skills include excellent operation and software development using statistical and engineering packages such as MatLab and R, programming skills in Perl, Java, PHP and MySQL and excellent familiarity with several bioinformatics data analysis tools encompassing a variety of data types (sequence, microarray and next generation sequencing data analysis) and usage and handling of biological databases.