Research themes

Our goal is to develop algorithms to discover knowledge from biomedical data and prior knowledge. We hope our algorithms are useful for biologists and clinicians to discover or test hypotheses using omics data such as genomics and transcripomics data. Specifically, we are developing

• Network inference algorithms to infer correlations and causal relationships from data and prior knowledge; and
• Network learning algorithms to learn important information (features) from networks.

Reseach Projects

Current funded projects

• 2016-20, deCODE - Cracking the Code of Adaptive Evolution (co-I, with J. Colborne et al.). £1,313,399 (3-year postdoc to CS)
• 2013-17, NanoMILE - Engineered nanomaterial mechanisms of interactions with living systems and the environment: a universal framework for safe nanotechnology (as Co-I, with E. Valsami-Jones et al.), EU FP7 (FP7-NMP-2012-LARGE-6). €9,624,979 (1-year postdoc to CS).
• 2015-17, International Exchanges Scheme: Learning in model space for cancer (as PI), The Royal Society (BIR002). £12,000
• 2015-17, The utility of mTOR signalling pathway dysregulation and mutational profiling in the risk stratification for future cognitive decline in MCI (as Co-I, with Z. Nagy et al.), Technology Strategy Board (TS/M010236/1). £368,657.
• 2015-17, Towards an integrated approach in defining the Mode of Action / Key Events of chemicals, Unilever (as Co-I, with M. Viant et al.). £450,040.

Prvious funded projects

• 2013-16, eGUT: a Tool for Predictive Computer Simulation of the Gut Microbiota and Host Interactions (as Co-I, with J. Kreft et al.), NC3Rs (NC/K000683/1). £332,745.
• 2013-16, Investigating the role of the mesenchymal stem cell phenotype in the pathogenesis of multiple myeloma (as Co-I, with D. A. Tennant et al.), Leukaemia & Lymphoma Research (13039). £183,099.
• 2015-16, EPSRC institutional fund: Achieving the earliest diagnosis of Cancer through a cascaded computational decision support system (PI). £12,000
• 2012-2014, Integrative biomarker discovery using computational intelligence (as PI), The Royal Society (IE111069). £12,000
• 2012-2013, MUSCLE: Multi-platform Unbiased-optimisation of Spectrometry via Closed Loop Experimentation (as Co-I, with M. R. Viant et al.), BBSRC (BB/I024085/1). £90,000 (9 month postdoc to CS, ~£35,000)
• 2012-2012, Novel Optimisation methods for metabolomics (as Co-I, with S. Decent et al.), EPSRC (EP/J01446X/1). £140,383 (£8,570 to CS)
• 2010-2011, Towards an agent-based modelling framework based on omics data for the investigation of cancer evolution (as PI), EPSRC Bridging the Gaps project awarded to the University of Birmingham. £14,926
• 2009-2010, Computational Intelligence for metabolomics and proteomics data analysis (as PI), the Wellcome Trust Value in People Awards Scheme. £27,592.
• 2008-2009, Automated metabolite identification and quantification using J-resolved NMR spectroscopy (as Researcher Co-Investigator, with Mark R. Viant et al.), BBSRC (BB/F016298/1), £92,700 (Approx. £25,000 to CS)
• 2007-2009, Leverhulme Early Career Fellowship, (as PI, success rate 7% - 8%), The Leverhulme Trust (ECF/2007/0433), £40,827