Celia M. T. Greenwood
McGill University
301 Papers
2.3K Citations
Celia M. T. Greenwood is an academic researcher from McGill University. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 51, co-authored 275 publications. Previous affiliations of Celia M. T. Greenwood include Cancer Care Ontario & Ontario Institute for Cancer Research.
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Papers
Estimating the effect-size of gene dosage on cognitive ability across the coding genome
Guillaume Huguet,Catherine Schramm,Elise Douard,Petra Tamer,Antoine Main,Pauline Monin,Jade England,Khadije Jizi,Thomas Renne,Myriam Poirier,Sabrina Nowak,Charles-Olivier Martin,Nadine Younis,Inga Sophia Knoth,Martineau Jean Louis,Zohra Saci,Maude Auger,Frédérique Tihy,Géraldine Mathonnet,Catalina Maftei,David J. Porteous,Gail Davies,Paul Redmond,Sarah E. Harris,Emmanuelle Lemyre,Gunter Schumann,Thomas Bourgeron,Zdenka Pausova,Tomáš Paus,Sherif Karama,Sarah Lippé,Ian J. Deary,Laura Almasy,Aurélie Labbe,David C. Glahn,Celia M. T. Greenwood,Sébastien Jacquemont +36 more
TL;DR: This first outline for the effect sizes of all coding genes on intelligence suggests that around 10,000 genes affect this trait.
Integrative analysis of gene expression data including an assessment of pathway enrichment for predicting prostate cancer.
TL;DR: By integrating information from the insulin signalling pathway into the prediction model, the authors achieved better prediction of prostate cancer and identified significant gene expression phenotypes that have the potential to characterize complex genetic alterations in prostate cancer.
6
A 10-color flow cytometry panel for diagnosis and minimal residual disease in chronic lymphocytic leukemia.
Alexandre Bazinet,Ryan N Rys,Amadou Barry,Celia M. T. Greenwood,Yoon Kow Young,Alma Mendoza,Ida LaPorta,Claudia M. Wever,Francois Mercier,Nathalie A. Johnson +9 more
TL;DR: In this paper, the authors added CD23 and CD200 to the EuroFlowT for diagnosis and minimal residual disease (MRD) monitoring of chronic lymphocytic leukemia (CLL) by flow cytometry.
6
Integrating Affymetrix microarray data sets using probe-level test statistic for predicting prostate cancer
Pingzhao Hu,Celia M. T. Greenwood,Joseph Beyene +2 more
- 01 Sep 2006
TL;DR: These analyses show that the prognostic gene expression signatures identified through the probe-level test statistics are more strongly differentially expressed and have better prediction accuracy than signatures derived from a probeset-level model.
6
The Genetic and Molecular Analyses of RAD51C and RAD51D Identifies Rare Variants Implicated in Hereditary Ovarian Cancer from a Genetically Unique Population
Wejdan M Alenezi,Larissa Milano,Caitlin T Fierheller,Corinne Serruya,Timothée Revil,Kathleen Klein Oros,Supriya Behl,Suzanna L. Arcand,Porangana Nayar,Dan Spiegelman,Simon Gravel,Anne-Marie Mes-Masson,Diane Provencher,William D. Foulkes,Zaki El Haffaf,Guy A. Rouleau,Luigi Bouchard,Celia M. T. Greenwood,Jean-Yves Masson,Jiannis Ragoussis,Patricia N. Tonin +20 more
TL;DR: The role of inherited variants in RAD51C and RAD51D, hereditary ovarian cancer risk genes, in French Canadians of Quebec, Canada exhibits a unique genetic landscape as shown by the frequency of carriers of specific rare pathogenic variants.