McGill initiative in Computational Medicine announces first cohort of projects funded through ResearchMatch

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Launched in March 2019 with a call for initial proposals, the ResearchMatch program of the McGill initiative in Computational Medicine (MiCM) was developed in an effort to better connect life science and clinical researchers with colleagues focused on data sciences.

“While some researchers have access to interesting datasets and questions, others are able to develop and apply quantitative methods to help look for answers,” explains Dr. Guillaume Bourque, Associate Professor in the Department of Human Genetics at McGill’s Faculty of Medicine and MiCM lead. “The challenge is that often the life science or clinical researchers don’t necessarily know where to find people with the right quantitative skills who are willing to collaborate and conversely data scientists don’t necessarily know who has interesting questions that they could help with. This challenge is what we aim to address through the creation of the ResearchMatch Program.”

Employing a unique approach meant to spark new collaborations, the ResearchMatch Program first asked the life science and clinical research community across the McGill network to provide submissions for initial project ideas. The data science community was invited to peruse the projects via the MiCM website, contact project leads for any initiative in which they had an interest and work together to submit a joint project proposal.

In total, 37 expressions of interest were received and 18 joint project proposals were submitted. Nine projects were ultimately selected for funding with support from the Faculty of Medicine, the McGill Interdisciplinary Initiative in Infection and Immunity, the Lady Davis Institute at the Jewish General Hospital and the Research Institute of the McGill University Health Centre.

The funded projects, which span areas including cancer, cardiovascular disease and pain, among others, will each receive funds meant to plan, organize and analyze existing data during the course of the next year.

“Clinicians often have innovative ideas to improve how they care for their patients. It can be challenging, however, for them to find experts in data science to work with to implement and evaluate their ideas,” explains Dr. David Buckeridge, Professor in the Department of Epidemiology, Biostatistics and Occupational Health and MiCM co-lead. “ResearchMatch creates this connection between experts in medicine and data science and provides seed funding to foster data-driven innovation to improve clinical care.”

The following is a list of funded projects in the first cohort of ResearchMatch:

Applicants Title Funded by
Nicolas Cermakian & David Langlais Genome-wide circadian regulation of gene expression in T cells McGill Initiative in Computational Medicine/McGill Interdisciplinary Initiative in Infection and Immunity
Luda Diatchenko & Sahir Rai Bhatnagar Genomewide Mega-Analysis of high quality phenotyped cohorts of temporomandibular disorders McGill Interdisciplinary Initiative in Infection and Immunity
Michael Witcher & Celia Greenwood New tools to characterize epigenomic reprogramming in cancer. Lady Davis Institute/McGill Initiative in Computational Medicine
Ariane Marelli & Yi Yang Quantitative modeling of the heart failure trajectories in patients with congenital heart disease The Research Institute of the McGill University Health Centre/McGill Initiative in Computational Medicine
Andrey Cybulsky & Amin Emad Signaling pathways and drug discovery in human glomerular diseases The Research Institute of the McGill University Health Centre/McGill Initiative in Computational Medicine
Amin Emad & William Pastor Identification of lineage-relevant transcriptional regulatory networks in human embryogenesis McGill Initiative in Computational Medicine
Stella Daskalopoulou & Nandini Dendukuri Quantification of the effect of SMOKing on artEriaL stiffnESS (SMOKELESS)  The Research Institute of the McGill University Health Centre/McGill Initiative in Computational Medicine
Amin Emad & Simon Rousseau Artificial Intelligence-informed molecular profiling of the frequency of pulmonary exacerbations in Cystic Fibrosis McGill Interdisciplinary Initiative in Infection and Immunity/McGill Initiative in Computational Medicine
Yue Li & Audrey Grant Integrative approach to dissect regulatory circuitry of pain-related phenotypes McGill Initiative in Computational Medicine

 

For more information on the MiCM and the ResearchMatch Program or to sign-up to the mailing list for other funding and training opportunities, visit: https://www.mcgill.ca/micm/

 

July 10, 2019

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