Gnimipieba Etienne
Ph.D., Biotechnology/Bioinformatics, University of Technology of Compiegne, France
MS, Computer Engineering and Mathematics for Integrative Biology, University of Evry Val d'Esonne, France
MS, Artificial Intelligence and Human Machine Interface, University of Yaounde, Cameroon BA,
Mathematics/Computer Science, University of Dschang, Cameroon
My research uses Systems Biology modeling and Data Mining approaches to aid in providing a better understanding of gene-disease interaction. Each of these two domains are limited in computing resources for a common research computing environment. The emergence of High Performance computing (HPC) infrastructures allow better handling of that dilemma. The long term goal is to develop a new decision support knowledge base for gene-disease study. This uses integrative approaches (algorithm, process, tools) for life science multi-scale systems integration and analysis using a combination of big data mining, machine learning and Systems Biology approaches. This includes 1) a novel reusable multi-scale data mining model for knowledge discovery based on adaptive machine learning and artificial intelligence; 2) new algorithms for data transformation and integration to handle the heterogeneity among the integrated data sources and Systems Biology data (images, text, relational data, etc.); 3) a flexible implementation easy to use tools on a HPC and big data infrastructure using R Bioconductor, Matlab, Java J2EE; 4) several Biological use case studies development.