Dr Nicos Angelopoulos
Senior Staff Scientist
This person is a member of Sanger Institute Alumni.
My main research interest lies in the application of computational statistics in the elucidation of cancer biology. The specific focus of my work is on knowledge based techniques, both, in approaches that derive abstract level information from data and in methods that incorporate prior knowledge in reasoning with new data. In this, my work seeks to bridge the areas of knowledge representation with those of modern applied statistics as seen in current computational biology and bioinformatics research. The foundations of my work are based on the use of logic programming as a prime tool for applied knowledge representation and Bayesian, model based algorithms for statistical inference.
Tyrosine kinase proteome in breast cancer cell lines (Imperial College)
Graphical models of focal adhesion dynamics. (Netherlands Cancer Institute)
Integrative statistics in logic programming (Netherlands Cancer Institute)
Bayesian ligand discovery (Edinburgh)
Co-development of Bayesian inference of model structure- theory & software (York)
Gained PhD in computer science (CIty University, London)