Assistant Professor

Mélanie Courtot

PhD, University of British Columbia

Ontario Institute for Cancer Research
MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario Canada M5G 0A3
Research Interests
Data Science and Computational Biology, Cancer Diagnosis and Therapy, Cancer Mechanisms and Models

Admin assistant: Michelle Xin

At A Glance

  • We build intelligent systems to leverage vast amounts of biomedical and biological data and answer research questions of importance to human health, biology, and society.
  • We promote data quality, integration and availability, and use big data to drive cancer innovations
  • Through international collaborations we drive development and implementation of community standards
  • Our large data platforms are used worldwide for pioneer projects in cancer and pathogen genomics as well as human cohort data
  • Diversity is at the core of the lab: we value diversity in lab members and projects!

Short Bio

I am the Director of Genome Informatics and a Principal Investigator at the Ontario Institute for Cancer Research (OICR). My 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.

I am passionate about translational informatics - building intelligent systems to gain new insights and impact human health. I co-lead the Clinical and Phenotypic workstream and Data Use and Cohort representation groups for the Global Alliance for Genomics and Health (GA4GH), as well as cohort harmonization efforts for the International HundredK+ Cohorts Consortium (IHCC).

Prior to joining OICR in January 2022, I was the metadata standards coordinator for the archival and infrastructure team at the European Bioinformatics Institute (EMBL-EBI), where I designed tools to streamline multi-omics submissions and developed integrated metadata strategies across the institute’s archival resources and other projects such as FAIRPlus, focusing on data quality, semantic enrichment, and standardization for pharmaceutical and cohort data respectively. I led the semantic harmonization work for the Common Infrastructure for National Cohorts in Europe, Canada, and Africa (CINECA) and the Davos Alzheimer’s Collaborative.

After receiving a BSc in Biochemistry and Master in Computer Science (2002) from the Université Louis Pasteur, in Strasbourg, France, I spent several years in different countries working as an international consultant/software developer. I rejoined academia in 2009 to start my PhD in Bioinformatics (graduated 2014) from the University of British Columbia, and did postdoctoral research at Simon Fraser University, before joining EMBL-EBI in June 2015 to lead the Gene Ontology (GO) editorial office and the Gene Ontology Annotation (GOA) projects.

I can be found on twitter, @mcourtot, where I often post about science, equity and diversity, food and silly things me or my children do.

Research Synopsis

Cancer precision medicine requires an accessible standardized dataset to deliver a functioning system with health and additional data (lifestyle, omic, etc). Achieving this vision - 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. 

My lab addresses these challenges by:

  1. Researching new methods for improving data quality, based on Machine Learning and Knowledge Representation, automated curation, and added-value data of high quality in particular for cancer related data.
  2. Enabling data integration at scale, in particular across human cohorts to provide standardized datasets amenable to further analyses. We aim 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.
  3. Deploying open source cloud based data platforms to make harmonized data discoverable, accessible and reusable globally. This supports our 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.

Recent Publications

  • Casolino R , Johns A L, Courtot M, Lawlor R T, De Lorenzo D, Horgan D, Mateo J, Normanno N, Rubin M, Stein L, Subbiah V, Westphalen B C, Lawler M, Park K, Perdomo S, Yoshino T, Wu J, Biankin A V. Accelerating cancer omics and precision oncology in health care and research: a Lancet Oncology Commission. The Lancet Oncology ( IF 54.433 ), DOI:10.1016/s1470-2045(23)00007-4.
  • Julius O Jacobsen, Michael Baudis, Gareth S Baynam, Jacques S Beckmann, Sergi Beltran, Orion J Buske, Tiffany J Callahan, Christopher G Chute, Mélanie Courtot, Daniel Danis, Olivier Elemento, Andrea Essenwanger, Robert R Freimuth, Michael A Gargano, Tudor Groza, Ada Hamosh, Nomi L Harris, Rajaram Kaliyaperumal, Kevin C Kent Lloyd, Aly Khalifa, Peter M Krawitz, Sebastian Köhler, Brian J Laraway, Heikki Lehväslaiho, Leslie Matalonga, Julie A McMurry, Alejandro Metke-Jimenez, Christopher J Mungall, Monica C Munoz-Torres, Soichi Ogishima, Anastasios Papakonstantinou, Davide Piscia, Nikolas Pontikos, Núria Queralt-Rosinach, Marco Roos, Julian Sass, Paul N Schofield, Dominik Seelow, Anastasios Siapos, Damian Smedley, Lindsay D Smith, Robin Steinhaus, Jagadish Chandrabose Sundaramurthi, Emilia M Swietlik, Sylvia Thun, Nicole A Vasilevsky, Alex H Wagner, Jeremy L Warner, Claus Weiland, Melissa A Haendel, Peter N Robinson. The GA4GH Phenopacket schema defines a computable representation of clinical data. Nature Biotechnology ( IF 68.164 ), DOI:10.1038/s41587-022-01357-4
  • Jonathan Lawson, Moran N Cabili, Giselle Kerry, Tiffany Boughtwood, Adrian Thorogood, Pinar Alper, Sarion R Bowers, Rebecca R Boyles, Anthony J Brookes, Matthew Brush, Tony Burdett, Hayley Clissold, Stacey Donnelly, Stephanie O M Dyke, Mallory A Freeberg, Melissa A Haendel, Chihiro Hata, Petr Holub, Francis Jeanson, Aina Jene, Minae Kawashima, Shuichi Kawashima, Melissa Konopko, Irene Kyomugisha, Haoyuan Li, Mikael Linden, Laura Lyman Rodriguez, Mizuki Morita, Nicola Mulder, Jean Muller, Satoshi Nagaie, Jamal Nasir, Soichi Ogishima, Vivian Ota Wang, Laura D Paglione, Ravi N Pandya, Helen Parkinson, Anthony A Philippakis, Fabian Prasser, Jordi Rambla, Kathy Reinold, Gregory A Rushton, Andrea Saltzman, Gary Saunders, Heidi J Sofia, John D Spalding, Morris A Swertz, Ilia Tulchinsky, Esther J van Enckevort, Susheel Varma, Craig Voisin, Natsuko Yamamoto, Chisato Yamasaki, Lyndon Zass, Jaime M Guidry Auvil, Tommi H Nyrönen, Mélanie Courtot. The Data Use Ontology to streamline responsible access to human biomedical datasets. Cell Genomics, DOI:10.1016/j.xgen.2021.100028.
  • Craig Voisin, Mikael Linde, Stephanie O M Dyke, Sarion R Bowers, Pinar Alper, Maxmillian P Barkley, David Bernick, Jianpeng Chao, Mélanie Courtot, Francis Jeanson, Melissa A Konopko, Martin Kuba, Jonathan Lawson, Jaakko Leinonen, Stephanie Li, Vivian Ota Wang, Anthony A Philippakis, Kathy Reinold, Gregory A Rushton, J Dylan Spalding, Juha Törnroos, Ilya Tulchinsky, Jaime M Guidry Auvil, Tommi H Nyrönen. GA4GH Passport standard for digital identity and access permissions. Cell Genomics, DOI:10.1016/j.xgen.2021.100030.
  • Annika Jacobsen, Ricardo de Miranda Azevedo, Nick Juty, Dominique Batista, Simon Coles, Ronald Cornet,  Mélanie Courtot, Mercè Crosas, Michel Dumontier, Chris T. Evelo, Carole Goble, Giancarlo Guizzardi, Karsten Kryger Hansen, Ali Hasnain, Kristina Hettne, Jaap Heringa, Rob W.W. Hooft, Melanie Imming, Keith G. Jeffery, Rajaram Kaliyaperumal, Martijn G. Kersloot, Christine R. Kirkpatrick, Tobias Kuhn, Ignasi Labastida, Barbara Magagna, Peter McQuilton, Natalie Meyers, Annalisa Montesanti, Mirjam van Reisen, Philippe Rocca-Serra, Robert Pergl, Susanna-Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Juliane Schneider, George Strawn, Mark Thompson, Andra Waagmeester, Tobias Weigel, Mark D. Wilkinson, Egon L. Willighagen, Peter Wittenburg, Marco Roos, Barend Mons, Erik Schultes. FAIR Principles: Interpretations and Implementation Considerations. Data Intelligence, 2020; 2 (1-2): 10–29. doi:
  • S. Carbon, E. Douglass, N. Dunn, B. Good, N.L. Harris, S.E. Lewis, C.J. Mungall, S. Basu, R.L. Chisholm, R.J. Dodson, E. Hartline, P. Fey, P.D. Thomas, L.P Albou, D. Ebert, M.J. Kesling, H. Mi, A. Muruganujan, X. Huang, S. Poudel, T. Mushayahama, J.C. Hu, S.A. LaBonte, D.A. Siegele, G. Antonazzo, H. Attrill, N.H. Brown, S. Fexova, P. Garapati, T.E.M. Jones, S.J. Marygold, G.H. Millburn, A.J. Rey, V. Trovisco, G. dos Santos, D.B. Emmert, K. Falls, P. Zhou, J.L. Goodman, V.B. Strelets, J. Thurmond, M. Courtot, D. Osumi-Sutherland, H. Parkinson, P. Roncaglia, M.L. Acencio, M. Kuiper, A. Lægreid, C. Logie, R.C. Lovering, R.P. Huntley, P. Denny, N.H. Campbell, B. Kramarz, V. Acquaah, S.H. Ahmad, H. Chen, J.H. Rawson, M. C. Chibucos, M. Giglio, S. Nadendla, R. Tauber, M.J. Duesbury, N Del-Toro, B.H.M. Meldal, L. Perfetto, P. Porras, S. Orchard, A. Shrivastava, Z. Xie, H.Y. Chang, R.D. Finn, A.L. Mitchell, N.D. Rawlings, L. Richardson, A. Sangrador-Vegas, J.A. Blake, K.R. Christie, M.E. Dolan, H.J. Drabkin, D.P. Hil, L. Ni, D. Sitnikov, M.A. Harris, S.G. Oliver, K. Rutherford, V. Wood, J. Hayles, J. Bahler, A. Lock, E.R. Bolton, J. De Pons, M. Dwinell, G.T. Hayman, S.J.F. Laulederkind, M. Shimoyama, M. Tutaj, S.-J. Wang, P. D’Eustachio, L. Matthews, J.P. Balhoff, S.A. Aleksander, G. Binkley, B.L. Dunn, J.M. Cherry, S.R. Engel, F. Gondwe, K. Karra, K.A. MacPherson, S.R. Miyasato, R.S. Nash, P.C. Ng, T.K. Sheppard, A. Shrivatsav VP, M. Simison, M.S. Skrzypek, S. Weng, E.D. Wong, M. Feuermann, P. Gaudet, E. Bakker, T.Z. Berardini, L. Reiser, S. Subramaniam, E. Huala, C. Arighi, A. Auchincloss, K. Axelsen, G., Argoud-Puy, A. Bateman, B. Bely, M.-C. Blatter, E. Boutet, L. Breuza, A. Bridge, R. Britto, H. Bye-A-Jee, C. Casals-Casas, E. Coudert, A. Estreicher, L. Famiglietti, P. Garmiri, G. Georghiou, A. Gos, N. Gruaz-Gumowski, E. Hatton-Ellis, U. Hinz, C. Hulo, A. Ignatchenko F. Jungo, G. Keller, K. Laiho, P. Lemercier, D. Lieberherr, Y. Lussi, A. MacDougall, M. Magrane, M. J. Martin, P. Masson, D.A. Natale, N. Hyka-Nouspikel, I. Pedruzzi, K. Pichler, S. Poux, C. Rivoire, M. Rodríguez-López, T. Sawford, E. Speretta, A. Shypitsyna, A. Stutz, S. Sundaram, M. Tognolli, N. Tyagi, K. Warner, R. Zaru, C. Wu, AD. Diehl, J. Chan, J. Cho, S. Gao, C. Grove, M.C. Harrison, K. Howe, R. Lee, J. Mendel, H.-M. Muller, D. Raciti, K. Van Auken*, M. Berriman, L. Stein, P. W. Sternberg, D. Howe, S. Toro, M. Westerfield. The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Research, DOI:10.1093/nar/gky1055.

Additional Publications listed on Google Scholar