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Institution

Université de Montréal

EducationMontreal, Quebec, Canada
About: Université de Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 45641 authors who have published 100476 publications receiving 4004007 citations. The organization is also known as: University of Montreal & UdeM.


Papers
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Journal ArticleDOI
TL;DR: Emphasis is placed on the new databases and the calculation and manipulation of phase diagrams and complex phase equilibria in the FactSage thermochemical software and databases.
Abstract: FactSage® was introduced in 2001 as the fusion of the F*A*C*T/FACT-Win and ChemSage thermochemical packages. The FactSage package runs on a PC operating under Microsoft Windows® and consists of a series of information, database, calculation and manipulation modules that enable one to access and manipulate pure substances and solution databases. With the various modules one can perform a wide variety of thermochemical calculations and generate tables, graphs and figures of interest to chemical and physical metallurgists, chemical engineers, corrosion engineers, inorganic chemists, geochemists, ceramists, electrochemists, environmentalists, etc. This paper presents a summary of the recent developments in the FactSage thermochemical software and databases. In the article, emphasis is placed on the new databases and the calculation and manipulation of phase diagrams and complex phase equilibria.

1,363 citations

Journal ArticleDOI
TL;DR: The innovations in block copolymer synthesis, polymeric micelle preparation and characterization, as well as the relevance of these developments to the field of biomedical research are proposed.

1,358 citations

Journal ArticleDOI
22 Jun 2018-Science
TL;DR: It is demonstrated that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine, and it is shown that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures.
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

1,357 citations

Journal ArticleDOI
TL;DR: The contaminant repository for affinity purification (the CRAPome) is presented and its use for scoring protein-protein interactions is described and aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol.
Abstract: Affinity purification coupled with mass spectrometry (AP-MS) is a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (for example, proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. The standard approach is to identify nonspecific interactions using one or more negative-control purifications, but many small-scale AP-MS studies do not capture a complete, accurate background protein set when available controls are limited. Fortunately, negative controls are largely bait independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the contaminant repository for affinity purification (the CRAPome) and describe its use for scoring protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely accessible at http://www.crapome.org/.

1,355 citations

Journal ArticleDOI
Andrew I R Maas1, David K. Menon2, P. David Adelson3, Nada Andelic4  +339 moreInstitutions (110)
TL;DR: The InTBIR Participants and Investigators have provided informed consent for the study to take place in Poland.
Abstract: Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Soderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbuchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigators

1,354 citations


Authors

Showing all 45957 results

NameH-indexPapersCitations
Yoshua Bengio2021033420313
Alan C. Evans183866134642
Richard H. Friend1691182140032
Anders Björklund16576984268
Charles N. Serhan15872884810
Fernando Rivadeneira14662886582
C. Dallapiccola1361717101947
Michael J. Meaney13660481128
Claude Leroy135117088604
Georges Azuelos134129490690
Phillip Gutierrez133139196205
Danny Miller13351271238
Henry T. Lynch13392586270
Stanley Nattel13277865700
Lucie Gauthier13267964794
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023118
2022485
20216,077
20205,753
20195,212
20184,696