Bioinformatics specialist with a background in molecular biology and biochemistry and ten years of experience in using statistics, machine learning, graph theory, programming, database management, and distributed computing techniques to answer bioinformatics and systems biology questions.
As the director of the Bioinformatics Core at Montana State University my objective is to help investigators on campus and elsewhere to design their experiments, process the data, and guide the interpretation of the results. This is achieved either using off-the-shelf toolkits, or by developing tailored pipelines whenever it is required for accuracy, scalability or speed purposes (see http://github.com/ajmazurie/)
Such collaborations typically involve
? the identification of candidate genes, proteins or compounds best discriminating (or predicting) experimental conditions as measured by various molecular assays: microarray, RNA-seq, ChIP-seq, mass spectrometry
? the interpretation of these candidate entities in terms of biological functions, first by combing genome, pathways and compound databases for relevant functional annotations, then by developing and deploying innovative algorithms to highlight biologically and statistically significant functional relationships among candidates
? the identification and scoring of correlation and causation in large 'omics datasets, using a combination of database development and ontologies for the data representation and query, and statistics, machine learning and graph theory to explore relationships among entities
As an assistant research professor in microbiology my research focuses on integrative biology topics such as regulation of biological processes, emergent behaviors of biological systems, and biological networks evolution and structure. I am also interested in the problem of biological knowledge representation and how algorithms can help investigators to semi-automatically expand on the knowledge accumulated on a model.