High-throughput technologies (such as microarrays and nextgeneration sequencing) produce massive amounts of data that prove valuable to researchers in understanding molecular and cellular processes. However, the large amounts of data produced by these technologies complicates their analysis.
Gwenael Leday’s research focuses on the development of scalable and flexible statistical methods, as well as software packages, to help address biological questions that arise from the analysis of microarray and sequencing data. Gwenael’s work includes the reconstruction of large-scale molecular regulatory networks, the joint analysis of multiple molecular data types and the incorporation of auxiliary information (prior knowledge) into statistical models.
A collaboration with the MRC Immunopsychiatry Consortium has led to the identification of immunological biomarkers of depression that show potential for the stratification of patients with major depressive disorder. Another, ongoing, collaboration uses data from ~700 members of the TwinsUK cohort to investigate how gene expression and metabolite levels in blood change over time, with the aim of supporting diagnosis and prediction of common chronic disease.