We provide expertise in computational biology ranging from applied statistics to computational and functional genomics
The Bioinformatics Core supports investigators in the Institute, the Department of Oncology and the Cancer Centre in all aspects of bioinformatics through state-of-the-art pipelines and advanced computational approaches. We support a broad range of projects from basic research to clinical trials, provide training and ensure coordination of experimental and analytics approaches through different phases of a research project. Increasingly, much of the research is related to individualised medicine such as *omics assessment of cancer patients, and the Core has a central role in enabling advancement and expansion of this new important area of research.
We focus on development and maintenance of cutting edge, robust and reproducible pipelines for genomics data analytics, development of new strategies for primary data analysis and interpretation, as well as on biological and clinical data integration to provide a richer and more comprehensive understanding of cancer aetiology and progression.
MDM2 (chr12:69,201,971–69,239,320) region amplification in bladder cancer (Cazier et al. 2014). Estimated copy number is indicated on the right-hand y axis; Single nucleotide variation allele frequencies are presented on the left-hand y axis.
Anastasia Samsonova received her PhD from Cambridge and the EMBL-EBI. In 2007, she became a postdoctoral fellow in the laboratory of Professor Norbert Perrimon, Department of Genetics, Harvard University, where she designed innovative computational strategies for *omics data analytics.
The modENCODE consortium (Samsonova AA) (2014). Nature 512, pp 445–448; “Comparative analysis of the transcriptome across distant species.”
Marchi, E., Kanapin, A., Magiorkinis, G. and Belshaw, R. (2014). J Virol 88, 9529–9537; “Unfixed endogenous retroviral insertions in the human pop.”
Cazier, J.-B. et al. (2014). Nat Commun 5, 3756; “Whole-genome sequencing of bladder cancers reveals somatic CDKN1A mutations and clinicopathological associations with mutation burden.”