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The lab studies gene and epigenomic regulatory processes that contribute to both normal physiology and disease pathology.


This includes the regulation of host defense mechanisms (related to antiviral, inflammatory, and anti-tumour responses), chromatin state changes underlying cellular senescence and ageing, and regulatory mechanisms underlying immune & inflammatory diseases, metabolic diseases and carcinogenesis.

There are two key focus areas of the lab:

Gain a mechanistic understanding of how immune phenotypes are actualised by studying information flow of cytokine signaling, metabolic and regulatory networks associated with these processes. We do this by identifying Upstream Regulators, Transcription Factor direct targets, Enhancer Promoter Interactions and associated chromatin architectural changes. The Interferon (IFN) system is used as a model with our bespoke IFN target genes and pathways resources combined with sophisticated computational algorithms that are being developed by us. We are also interested in regulatory processes underlying cellular senescence and ageing. Particularly epigenomic and chromatin regulations and the discovery of senolytic and senomorphic biomarkers.

Another key aspect of our work is in understanding carcinogenesis and metastasis. 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. We are particularly interested in early detection and diagnosis of cancer.


The Samarajiwa lab integratively studies gene (transcriptome and translatome), epigenome and chromatin architecture regulation affecting disease processes and phenotypes at the systems level. We utilise a mixture of Computational & Systems Biology, Genomics and Data Science (especially leading edge Artificial Intelligence methods) to integrate, data-mine and de-convolute large, complex and heterogeneous 'omic' datasets (extracted from data repositories or generated by us, and our numerous experimental and clinical collaborators) with the aim of identifying fundamental rules and regulatory logic underlying gene and (epi)genome regulation of disease processes.


Guest Lecture, Imperial College London: "AI in Biomedicine: Now and The Future", January 9th, 2024, 1.30 PM

Cambridge Centre for Innovation and Development "The Application of Artificial Intelligence and Data Science in Biomedicine" February 9th, 2021

Genomics & AI: 3d Cambridge Genomics Meetup "Data Science Approaches for Cancer Epigenomics" January 22nd, 2020


BBC digital planet interview (begins 6.15 minutes into programme)

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

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