Maysson holds a PhD in Bioinformatics and BEng in Software Engineering and Information Systems.
After completing her PhD in 2013 at the Buckingham Institute for Translational Medicine (BITM), University of Buckingham, she joined the BITM as a Postdoctoral Research Fellow in Bioinformatics for three years. Her key research interest was focusing on biological data analysis and developing algorithms for pathway enrichment and biomarkers Identification using gene expression data. During and after her PhD (2011-2014), she was teaching “Introduction to Statistics” module at the School of Computing, University of Buckingham.
Maysson moved to the Nuffield Department of Population Health, Big Data Institute, University of Oxford in 2016 as a Research Fellow in Bioinformatics and then as a Senior Research Fellow in 2017. Since then, she is leading the Bioinformatics work in a multidisciplinary team where her key research focuses on analysing genetic data from large scale Biobanks (e.g. UK Biobank) and clinical trial studies such as REVEAL, SHARP, and THRIVE to identify and understand genetic determinants of complex diseases such as cardiovascular disease. Her research includes developing and using analytical pipelines that incorporate machine learning algorithms to enhance the analysis and provide better understanding of big data.
Maysson joined the School of Computing at Buckingham in 2020 as a part-time Lecturer in Computer Science along with her research role at Oxford. She is the module lead for the Data Exploration and Visualisation, and Systems and Tools for Data Science in the MSc Applied Data Science programme.
Selected publications
- Ibrahim M. “Pathways Enrichment Analysis of Gene Expression Data in Type 2 Diabetes”. Methods Mol Biol. 2020; 2076:119-128. doi:10.1007/978-1-4939-9882-1_7
- Hopewell JC, Ibrahim M, Hill M, Shaw PM, Braunwald E, Blaustein RO, Bowman L, Landray MJ, Sabatine MS, Collins R; HPS3/TIMI55 – REVEAL Collaborative Group. “Impact of ADCY9 Genotype on Response to Anacetrapib”, Circulation. 23 Jul 2019
- Stiby AI, Camm CF, Ibrahim M, Offer A, Bulbulia R, Clarke R, Parish S, Armitage J, Hopewell JC “Genetic approaches to elucidating our understanding of therapeutic targets”, Li Ka Shing Symposium, Oxford, 1st Sep 2017
- Ibrahim, M., Jassim, S., Cawthorne, M. A., & Langlands, K. “A MATLAB tool for pathway enrichment using a topology-based pathway regulation score”, BMC bioinformatics Journal, 2014, 15(1), 358.
- Ibrahim, M., Selway, J., Chin, K., Jassim, S., Cawthorne, M A., and Langlands, K., “Rational Identification of Prognostic Markers of Breast Cancer”, The International Conference on Bioinformatics Models, Methods and Algorithms. 2-6 March 2014
- Ibrahim, M., Jassim, S., Cawthorne, M.A. and Langlands, K, “A topology-based score for pathway enrichment”, Journal of computational biology, May 2012, 19 (5), pp. 563-574.
- Ibrahim, M., Jassim, S., Cawthorne, M.A. and Langlands, K, “Integrating pathway enrichment and gene network analysis provides accurate disease classification”, In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Portugal, 1st – 4th Feb 2012, pp. 156-163
- Ibrahim, M., Jassim, S., Cawthorne, M.A. and Langlands, K, “A pathway-based gene selection method provides accurate disease classification”, International Journal of Digital Society (IJDS), 2011, 2 (4), pp. 566 – 573.
- Ibrahim, M., Jassim, S., Cawthorne, M.A. and Langlands, K, “Pathway-based gene selection for disease classification”, International Conference on Information Society (i-Society), London, UK, 2011, pp. 360-365.