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Dr Graham HAMILTON - Lead Bioinformatician

Photograph of Polyomics staff member

Graham Hamilton is the Lead Bioinformatician at Glasgow Polyomics. His expertise lies in the analysis of Next Generation Sequence data. He has extensive experience in the design and analysis of RNA-Seq, de novo assembly and annotation, whole genome variant discovery, targeted variant discovery, ChIP seq, metagenomics and ribosomal profiling experiments.

Graham has a Ph.D in molecular genetics and a Masters degree in Information Technology from the University of Glasgow.





Selected Publications

  • Monica Tsimbouri, Kate Murawski, Graham Hamilton, Pawel Herzyk, Richard O.C. Oreffo & Nikolaj Gadegaard, Matthew J. Dalby. A genomics approach in determining nanotopographical effects on MSC phenotype. Biomaterials, 34(9), pp.2177–2184.
  • Wiejak J, Tsimbouri PM, Herzyk P, Dalby MJ, Hamilton G, Yarwood SJ. (2013). Genomic analysis of the role of transcription factor C/EBPδ in the regulation of cell behaviour on nanometric grooves. Biomaterials, 34(8), pp.1967–1979.
  • Stangherlin A, Gesellchen F, Zoccarato A, Terrin A, Fields LA, Berrera, M, Surdo, NC, Craig MA, Smith G, Hamilton G, Zaccolo M. cGMP signals modulate cAMP levels in a compartment-specific manner to regulate catecholamine-dependent signaling in cardiac myocytes. Circulation Research 2011; 108: 929-939.

Grants Awarded

  • n-depth assessment of the healthy canine oral microbiome using high-throughput (metagenomic) sequencing. Marcello P Riggio, David Bennett and Graham Hamilton. The Kennel Club Charitable Trust.
  • A polyomics based approach to identify molecular pathways and genetic modifiers which influence the development of stroke caused by collagen IV mutations, ISSF.Exome Sequencing for the Genetic Diagnosis of Rare Diseases: Fostering a New Working Relationship between the NHS, the University of Glasgow and Glasgow Polyomics, ISSF.
  • Detecting population trends for tick-borne pathogens from genomic data: new tools for managing Lyme disease in Scotland, ISSF.
  • Using bacterial phylogenomics to reveal contemporary population dynamics and their underlying drivers for a major tick-bourne pathogen, NERC.