Dr. Mélanie Courtot’s team develops new software, databases and other necessary components to store, organize and compute over the large and complex datasets being generated by OICR’s cancer research programs. She is passionate about translational informatics — building intelligent systems to gain new insights and impact human health.
Cancer precision medicine requires an accessible, standardized dataset to deliver a functioning system with health and additional data (lifestyle, omic, etc.). Achieving this vision of a globally shared knowledge ecosystem to advance science and improve health for all requires high-quality data, robust data integration processes at scale and discovery platforms providing data access across international borders.
Courtot’s lab addresses these challenges by:
- Researching new methods for improving data quality, based on machine learning and knowledge representation, automated curation and added-value data of high quality for cancer related data.
- Enabling data integration at scale, across human cohorts, to provide standardized datasets amenable to further analyses. The lab aims to understand whether we can better predict patients’ health outcomes and will encompass defining standards and computable data patterns such as phenotypes that can be used across research and EHR datasets.
- Deploying open-source cloud-based data platforms to make harmonized data discoverable, accessible and reusable globally. This supports work on phenomics — associating phenotypes and environmental factors to patients’ genotypes to elucidate genomic etiology of diseases, improve diagnosis and prognosis and enable personalized medicine.
- Project lead and metadata standards coordinator, EMBL-EBI, Cambridge, UK, 2015-2022
- Post-doctoral fellow, Simon Fraser University and BC CDC, Vancouver, Canada, 2014-2015
- Ph.D., Bioinformatics, University of British Columbia, Vancouver, Canada, 2009‑2014
- Bioinformatics specialist, Vancouver, Canada, 2007-2009
- Software engineer, France, UK, Greece, 2002-2007
- M.Sc., Computer Science, Université Louis Pasteur, Strasbourg, France, 2002
- B.Sc., Structural Biochemistry, Université Louis Pasteur, Strasbourg, France, 2001
- Director Genome Informatics and Principal Investigator, OICR
- Assistant Professor, Medical Biophysics department, University of Toronto
- Member of the Global Alliance for Genomics and Health (GA4GH) Steering Committee
- Casolino R, Johns AL, Courtot M, Lawlor RT, De Lorenzo F, Horgan D, Mateo J, Normanno N, Rubin M, Stein L, Subbiah V, Westphalen BC, Lawler M, Park K, Perdomo S, Yoshino T, Wu J, Biankin AV; Lancet Oncology Commission on Cancer Omics and Precision Oncology. Accelerating cancer omics and precision oncology in health care and research: a Lancet Oncology Commission. Lancet Oncol. 2023 Feb;24(2):123-125. doi: 10.1016/S1470-2045(23)00007-4. PMID: 36725142.
- Jacobsen, J.O.B., Baudis, M., Baynam, G.S. et al. The GA4GH Phenopacket schema defines a computable representation of clinical data. Nat Biotechnol 40, 817–820 (2022). https://doi.org/10.1038/s41587-022-01357-4
- Lawson, J., Cabili, M. N., Kerry, G., Boughtwood, T. F., Thorogood, A., Alper, P., Bowers, S. R., Boyles, R., Brookes, A. J., Brush, M. H., Burdett, T., Clissold, H. L., Donnelly, S., Dyke, S. O.M., Freeberg, M. A., Haendel, M. A., Hata, C., Holub, P., Jeanson, F., Jené, A., Kawashima, M., Kawashima, S., Konopko, M. A., Kyomugisha, I., Li, H., Linden, M., Rodriguez, L. L., Morita, M., Mulder, N., Muller, J., Nagaie, S., Nasir, J., Ogishima, S., Ota Wang, V., Paglione, L. A.D., Pandya, R. N., Parkinson, H. E., Philippakis, A. A., Prasser, F., Rambla, J., Reinold, K., Rushton, G. A., Saltzman, A., Saunders, G. I., Sofia, H. J., Spalding, J. D., Swertz, M. A., Tulchinsky, I., van Enckevort, E. J., Varma, S., Voisin, C., Yamamoto, N., Yamasaki, C., Zass, L. J., Guidry Auvil, J. M., Nyrönen, T. H. and Courtot, M. (2021) The Data Use Ontology to streamline responsible access to human biomedical datasets. Cell Genomics. 1(2), None. 2666-979X.
- Jacobsen A, de Azevedo RM, Juty N, Batista D, Coles S, Cornet R, Courtot M, Crosas M, Dumontier M, et al. FAIR principles: Interpretations and implementation considerations. Data Intelligence. 2020;2 (1-2) :10-29.
- The Gene Ontology Consortium, The Gene Ontology Resource: 20 years and still Going strong, Nucleic Acids Research, Volume 47, Issue D1, 08 January 2019, Pages D330–D338, https://doi.org/10.1093/nar/gky1055
Selected semantic-based tools
- Ontobee for ontology browsing
- Ontofox for ontology term reuse
- Biovalidator for ontology-based semantic validation
- flowCL for ontology-based labelling of cell populations in flow cytometry
Selected knowledge representation standards
- Phenopacket schema, a structured format for phenoptyic metadata exchange
- GA4GH Passport enables global researcher authentication
- GA4GH Data Use Ontology for consistent representation of data use conditions
- Gene Ontology, the most widely used ontology worldwide to represent functions of genes and their products