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 :