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Institution

Université de Sherbrooke

EducationSherbrooke, Quebec, Canada
About: Université de Sherbrooke is a education organization based out in Sherbrooke, Quebec, Canada. It is known for research contribution in the topics: Population & Receptor. The organization has 14922 authors who have published 28783 publications receiving 792511 citations. The organization is also known as: Universite de Sherbrooke & Sherbrooke University.


Papers
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Journal ArticleDOI
TL;DR: This work considers the application of the minimum message length (MML) principle to determine the number of clusters in a finite mixture model based on the generalized Dirichlet distribution.
Abstract: We consider the problem of determining the structure of high-dimensional data without prior knowledge of the number of clusters. Data are represented by a finite mixture model based on the generalized Dirichlet distribution. The generalized Dirichlet distribution has a more general covariance structure than the Dirichlet distribution and offers high flexibility and ease of use for the approximation of both symmetric and asymmetric distributions. This makes the generalized Dirichlet distribution more practical and useful. An important problem in mixture modeling is the determination of the number of clusters. Indeed, a mixture with too many or too few components may not be appropriate to approximate the true model. Here, we consider the application of the minimum message length (MML) principle to determine the number of clusters. The MML is derived so as to choose the number of clusters in the mixture model that best describes the data. A comparison with other selection criteria is performed. The validation involves synthetic data, real data clustering, and two interesting real applications: classification of Web pages, and texture database summarization for efficient retrieval.

156 citations

Journal ArticleDOI
TL;DR: It is speculated that ALA and EPA may well have useful supporting roles in maintaining brain function during aging but not by their conversion to DHA, as ALA is an efficient ketogenic fatty acid, while EPA promotes fatty acid oxidation.
Abstract: The maintenance of optimal cognitive function is a central feature of healthy aging. Impairment in brain glucose uptake is common in aging associated cognitive deterioration, but little is known of how this problem arises or whether it can be corrected or bypassed. Several aspects of the challenge to providing the brain with an adequate supply of fuel during aging seem to relate to omega-3 fatty acids. For instance, low intake of omega-3 fatty acids, especially docosahexaenoic acid (DHA), is becoming increasingly associated with several forms of cognitive decline in the elderly, particularly Alzheimer's disease. Brain DHA level seems to be an important regulator of brain glucose uptake, possibly by affecting the activity of some but not all the glucose transporters. DHA synthesis from either α-linolenic acid (ALA) or eicosapentaenoic acid (EPA) is very low in humans begging the question of whether these DHA precursors are likely to be helpful in maintaining cognition during aging. We speculate that ALA and EPA may well have useful supporting roles in maintaining brain function during aging but not by their conversion to DHA. ALA is an efficient ketogenic fatty acid, while EPA promotes fatty acid oxidation. By helping to produce ketone bodies, the effects of ALA and EPA could well be useful in strategies intended to use ketones to bypass problems of impaired glucose access to the brain during aging. Hence, it may be time to consider whether the main omega-3 fatty acids have distinct but complementary roles in brain function.

156 citations

Journal ArticleDOI
TL;DR: The impact of NuA4-dependent acetylation on SWR1-driven incorporation of H2A.Z into chromatin is investigated, and depletion experiments indicate that the bromodomain-containing protein Bdf1 is important for NuA 4-dependent stimulation ofSWR1.

156 citations

Journal ArticleDOI
TL;DR: Gas dispersion in a laboratory scale (5 L) stirred bioreactor is modelled using a commercial computational fluid dynamics (CFD) code FLUENT 6.2 to predict spatial distribution of gas hold-up, Sauter mean bubble diameter, gas–liquid mass transfer coefficient and flow structure.

156 citations


Authors

Showing all 15051 results

NameH-indexPapersCitations
Masashi Yanagisawa13052483631
Joseph V. Bonventre12659661009
Jeffrey L. Benovic9926430041
Alessio Fasano9647834580
Graham Pawelec8957227373
Simon C. Robson8855229808
Paul B. Corkum8857637200
Mario Leclerc8837435961
Stephen M. Collins8632025646
Ed Harlow8619061008
William D. Fraser8582730155
Jean Cadet8337224000
Vincent Giguère8222727481
Robert Gurny8139628391
Jean-Michel Gaillard8141026780
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202384
2022189
20211,858
20201,805
20191,625
20181,543