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Novel bioinformatics approach to investigate quantitative phenotype-genotype associations in neuroimaging studies
Sejal Patel, Min Tae M. Park, The Alzheimer’s Disease Neuroimaging Initiative, M. Mallar Chakravarty, Jo Knight
doi: https://doi.org/10.1101/015065
Sejal Patel
1Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
2Institute of Medical Science, University of Toronto, Toronto, ON, Canada
Min Tae M. Park
3Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Verdun, QC, Canada
4Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
M. Mallar Chakravarty
3Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Verdun, QC, Canada
5Department of Psychiatry, McGill University, Montreal, QC, Canada
Jo Knight
1Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
2Institute of Medical Science, University of Toronto, Toronto, ON, Canada
6Department of Psychiatry, University of Toronto, Toronto, ON, Canada
7Dalla Lana School of Public Health, Biostatistics Division, University of Toronto, Toronto, ON, Canada
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Posted February 10, 2015.
Novel bioinformatics approach to investigate quantitative phenotype-genotype associations in neuroimaging studies
Sejal Patel, Min Tae M. Park, The Alzheimer’s Disease Neuroimaging Initiative, M. Mallar Chakravarty, Jo Knight
bioRxiv 015065; doi: https://doi.org/10.1101/015065
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