Institution
University of Rouen
Education•Rouen, France•
About: University of Rouen is a education organization based out in Rouen, France. It is known for research contribution in the topics: Population & Receptor. The organization has 7299 authors who have published 13209 publications receiving 313477 citations.
Topics: Population, Receptor, Laser, Atom probe, Membrane
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a review of nanostructural features of nickel-based superalloys as revealed by Field-Ion Microscopy, Atom Probe (APFIM), and 3D Atom Probe are reviewed.
105 citations
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TL;DR: Two categories of antigens, enzymes of the glycolytic family and molecular chaperones are also targeted by the early untreated RA autoantibody response, and notably the FUSE-BPs, citrullination is involved in the immunological tolerance breakdown observed earlier in RA patients.
Abstract: Introduction
The aim of our study was to identify new early rheumatoid arthritis (RA) autoantibodies.
105 citations
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14 Jun 2009TL;DR: It is shown that better subsets of decision trees can be obtained even using a sub-optimal classifier selection method, which proves that “classical” RF induction process, for which randomized trees are arbitrary added to the ensemble, is not the best approach to produce accurate RF classifiers.
Abstract: In this paper we present a study on the Random Forest (RF) family of ensemble methods. In a “classical” RF induction process a fixed number of randomized decision trees are inducted to form an ensemble. This kind of algorithm presents two main drawbacks : (i) the number of trees has to be fixed a priori (ii) the interpretability and analysis capacities offered by decision tree classifiers are lost due to the randomization principle. This kind of process in which trees are independently added to the ensemble, offers no guarantee that all those trees will cooperate effectively in the same committee. This statement rises two questions : are there any decision trees in a RF that provide the deterioration of ensemble performance? If so, is it possible to form a more accurate committee via removal of decision trees with poor performance? The answer to these questions is tackled as a classifier selection problem. We thus show that better subsets of decision trees can be obtained even using a sub-optimal classifier selection method. This proves that “classical” RF induction process, for which randomized trees are arbitrary added to the ensemble, is not the best approach to produce accurate RF classifiers. We also show the interest in designing RF by adding trees in a more dependent way than it is traditionally done in “classical” RF induction algorithms.
105 citations
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TL;DR: The studies have shown that the transmembrane domain of AtXylT and its short flanking amino acid sequences are sufficient to specifically localize a reporter protein to the medial Golgi cisternae in tobacco cells.
Abstract: Characterization of a beta1,2-xylosyltransferase from Arabidopsis thaliana (AtXylT) was carried out by expression in Sf9 insect cells using a baculovirus vector system. Serial deletions at both the N- and C-terminal ends proved that integrity of a large domain located between amino acid 31 and the C-terminal lumenal region is required for AtXylT activity expression. The influence of N-glycosylation on AtXylT activity has been evaluated using either tunicamycin or mutagenesis of potential N-glycosylation sites. AtXylT is glycosylated on two of its three potential N-glycosylation sites (Asn51, Asn301, Asn478) and the occupancy of at least one of these two sites (Asn51 and Asn301) is necessary for AtXylT stability and activity. Contribution of the N-terminal part of AtXylT in targeting and intracellular distribution of this protein was studied by expression of variably truncated, GFP-tagged AtXylT forms in tobacco cells using confocal and electron microscopy. These studies have shown that the transmembrane domain of AtXylT and its short flanking amino acid sequences are sufficient to specifically localize a reporter protein to the medial Golgi cisternae in tobacco cells. This study is the first detailed characterization of a plant glycosyltransferase at the molecular level.
105 citations
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TL;DR: In this article, the basic principles and limitations of classical preferential crystallization and its applications on "exotic" systems by an extensive usage of phase diagrams are discussed, and the implementation of continuous "gentle" grinding can solve the main problem of this method, i.e., the nucleation of the counter enantiomer.
Abstract: The mirror symmetry relationship between enantiomers makes their separations by ‘classical’ separation methods difficult. When applicable, preferential crystallization is a productive and cost effective process which consists of alternate crystallizations of both enantiomers crystallizing as a conglomerate. Addition of in situ racemization to ‘classical’ preferential crystallization allows the yield to increase up to 100% in a single batch operation. Furthermore, the implementation of continuous ‘gentle’ grinding can solve the main problem of this method, i.e. the nucleation of the counter enantiomer. Preferential crystallization methodology can be also applied to any system composed of non symmetrical species. However, a set of thermodynamic and kinetic parameters must be determined for every compound that is supposed to crystallize selectively. This ‘highlight’ details the basic principles and the limitations of ‘classical’ preferential crystallization and its applications on ‘exotic’ systems by an extensive usage of phase diagrams.
105 citations
Authors
Showing all 7360 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yves Agid | 141 | 669 | 74441 |
Alexis Brice | 135 | 870 | 83466 |
Mohamed Eddaoudi | 94 | 327 | 64217 |
Hervé Tilly | 86 | 479 | 30321 |
David Cohen | 83 | 635 | 37722 |
Jörg Neugebauer | 81 | 491 | 30909 |
Hubert Vaudry | 80 | 975 | 34350 |
Michel Baudry | 80 | 372 | 23890 |
Richard L. Stevens | 79 | 264 | 19148 |
Claudine Berr | 75 | 297 | 27919 |
Christian P. Robert | 75 | 535 | 36864 |
Thierry Frebourg | 71 | 307 | 22403 |
Georges Pelletier | 69 | 432 | 19018 |
Michel Vert | 69 | 333 | 17899 |
Jean-Charles Schwartz | 69 | 252 | 15917 |