Application of statistical and computational methods in molecular biology. Analysis of noisy, high-dimensional data with a specific focus on network inference, variable selection and clustering.Applications include inference of causal protein signalling networks, drug response prediction and disease subtype discovery.
Selected PapersAkbani R, Ng PKS, Werner HMJ, . . . , Hill SM, . . . , Mukherjee S, Lu Y, Mills GB. (2014)A pan-cancer proteomic perspective on the Cancer Genome Atlas.
Nature Communications : (to appear)
Hill SM, Lu Y, Molina J, Heiser LM, Spellman PT, Speed TP, Gray JW, Mills GB, and Mukherjee S. (2012)Bayesian inference of signaling network topology in a cancer cell line.
Bioinformatics 28: 2804-2810
Hill SM, Neve RM, Bayani N, Kuo W-L, Ziyad S, Spellman PT, Gray JW, and Mukherjee S. (2012)Integrating biological knowledge into variable selection: An empirical Bayes approach with an application in cancer biology.
BMC Bioinformatics 13: 94
Hill SM. (2012)Sparse Graphical Models for Cancer Signalling.
PhD thesis, University of Warwick, UK :