Cancer is a collection of over 200 different diseases (most with multiple subtypes) characterized by abnormal cell growth, deregulated proliferation, and tissue invasion. Its evolutionary nature, the resultant heterogeneity within and between tumours, together with complex interactions with the microenvironment, lead to difficulty in treating or finding a cure. Perturbation in cellular information flow due to mutations, genetic aberrations, ploidy, metabolic reprogramming and cellular pathway and network deregulation, result in complex phenotypes that promote carcinogenesis. The Samarajiwa lab integratively studies gene (transcriptome and translatome), epigenome and chromatin architecture regulation affecting these carcinogenic processes and phenotypes at the systems level.
We utilise a mixture of Computational & Systems Biology, Genomics and Data Science (including Artificial Intelligence methods) to integrate, data-mine and de-convolute large, complex and heterogeneous cancer 'omic' datasets (extracted from data repositories or generated by our numerous experimental and clinical collaborators) with the aim of identifying fundamental rules underlying gene and (epi)genome regulation of carcinogenic processes.
Genomics & AI: 3d Cambridge Genomics Meetup "Data Science Approaches for Cancer Epigenomics" January 22nd, 2020
Pint of Science Cambridge 2019: "Can AI help in the fight against cancer?" - Monday 20th May 7.00-9.30 pm
Cambridge Science Festival 2019: "Artificial Intelligence assisted discovery in the battle against cancer and other diseases" - Sunday 24th March 2.30 pm