Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Emilie Neveu"'
Autor:
Aude Parcelier, Julien Buisset, Emilie Neveu, Bastien Kauffmann, Sandrine Fraboulet, Peggy Sanatine, Samia Martin, C?drick Rousseaux, Nadia Avenier, Sabine Charrier
Publikováno v:
Re:GEN Open, Vol 2, Iss 1, Pp 28-36 (2022)
Background: In the context of ex vivo gene therapy or chimeric antigen receptor T cell (CAR-T) cell therapy, vector copy number (VCN) analysis in transduced cells by lentiviral vectors enables the assessment of risk and therapeutic efficiency in pati
Externí odkaz:
https://doaj.org/article/1891b6ea0fe24f2fbad1c22dc45dcd7f
Autor:
Leonid L. Moroz, Dirk Fasshauer, Emilie Neveu, Frederique Varoqueaux, Daria Y. Romanova, Andrea B. Kohn, Mikhail A. Nikitin, Dosung Sohn
Publikováno v:
Scientific reports, vol. 10, no. 1, pp. 13020
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Nitric oxide (NO) is a ubiquitous gaseous messenger, but we know little about its early evolution. Here, we analyzed NO synthases (NOS) in four different species of placozoans—one of the early-branching animal lineages. In contrast to other inverte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a596aebbc5ab476316096c5380d861e2
https://serval.unil.ch/notice/serval:BIB_3BE4C833620A
https://serval.unil.ch/notice/serval:BIB_3BE4C833620A
Autor:
Michael G. Jacox, William J. Crawford, Jerome Fiechter, Andrew M. Moore, Emilie Neveu, Christopher A. Edwards
Publikováno v:
Deep Sea Research Part II: Topical Studies in Oceanography. 151:16-36
Low frequency variability of the California Current System (CCS) is investigated using circulation estimates based on a 31-year (1980–2010) sequence of historical analyses of the CCS calculated using the Regional Ocean Modeling System (ROMS) 4-dime
Publikováno v:
Bioinformatics
Bioinformatics, 2016, 32 (7), pp.i693-i701. ⟨10.1093/bioinformatics/btw443⟩
Bioinformatics, Oxford University Press (OUP), 2016, 32 (7), pp.i693-i701. ⟨10.1093/bioinformatics/btw443⟩
Bioinformatics, 2016, 32 (7), pp.i693-i701. ⟨10.1093/bioinformatics/btw443⟩
Bioinformatics, Oxford University Press (OUP), 2016, 32 (7), pp.i693-i701. ⟨10.1093/bioinformatics/btw443⟩
Motivation Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expa
Autor:
Emma Nuss, Andrew M. Moore, Christopher A. Edwards, Emilie Neveu, Patrick T. Drake, Jerome Fiechter, Michael G. Jacox, William J. Crawford
Publikováno v:
Ocean Modelling. 99:133-151
The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation tool has been used to compute two sequences of circulation analyses for the U.S. west coast. One sequence of analyses spans the period 1980–2010 and is s
Autor:
Grégoire Danoy, Petr Popov, Angelo Migliosi, Emilie Neveu, Pascal Bouvry, Xavier Besseron, Sergei Grudinin, Alexandre Hoffmann
Publikováno v:
Bioinformatics
Bioinformatics, 2018, 34 (16), pp.2757-2765. ⟨10.1093/bioinformatics/bty160⟩
BASE-Bielefeld Academic Search Engine
Bioinformatics, Oxford University Press (OUP), 2018, 34 (16), pp.2757-2765. ⟨10.1093/bioinformatics/bty160⟩
Bioinformatics, 2018, 34 (16), pp.2757-2765. ⟨10.1093/bioinformatics/bty160⟩
BASE-Bielefeld Academic Search Engine
Bioinformatics, Oxford University Press (OUP), 2018, 34 (16), pp.2757-2765. ⟨10.1093/bioinformatics/bty160⟩
Motivation The root mean square deviation (RMSD) is one of the most used similarity criteria in structural biology and bioinformatics. Standard computation of the RMSD has a linear complexity with respect to the number of atoms in a molecule, making
Autor:
Eichiro Ichiishi, Dmitri Beglov, Bernard Maigret, Gyu Rie Lee, Artem B. Mamonov, Shoshana J. Wodak, Jonathan C. Fuller, Dima Kozakov, Jong Young Joung, Petr Popov, Xiaofeng Yu, Keehyoung Joo, João P. G. L. M. Rodrigues, Anna Vangone, Koen M. Visscher, Xiaoqin Zou, Paul A. Bates, Andriy Kryshtafovych, Shourya S. Roy Burman, Daisuke Kihara, Romina Oliva, Efrat Ben-Zeev, Jeffrey J. Gray, Yang Shen, Li C. Xue, Sameer Velankar, Emilie Neveu, Shruthi Viswanath, Dina Schneidman-Duhovny, Juan Esquivel-Rodríguez, Mieczyslaw Torchala, Amit Roy, Alexandre M. J. J. Bonvin, David R. Hall, Tanggis Bohnuud, Xusi Han, David W. Ritchie, Ron Elber, Daisuke Kuroda, Zhiwei Ma, Joan Segura, Carlos A. Del Carpio, Nicholas A. Marze, Jong Yun Kim, Andrej Sali, Petras J. Kundrotas, Ezgi Karaca, Neil J. Bruce, Chaok Seok, Panagiotis L. Kastritis, Shen You Huang, Ilya A. Vakser, Lim Heo, Sanbo Qin, Raphael A. G. Chaleil, Adrien S. J. Melquiond, Miguel Romero-Durana, Anisah W. Ghoorah, Surendra S. Negi, Andrey Tovchigrechko, Françoise Ochsenbein, Narcis Fernandez-Fuentes, Liming Qiu, Miriam Eisenstein, Mehdi Nellen, Marie-Dominique Devignes, Lenna X. Peterson, Jinchao Yu, Minkyung Baek, Brian G. Pierce, Hasup Lee, Toshiyuki Oda, Rebecca C. Wade, Raphael Guerois, Juan Fernández-Recio, Iain H. Moal, Edrisse Chermak, Sergei Grudinin, Sangwoo Park, Ivan Anishchenko, Chengfei Yan, Thom Vreven, Kentaro Tomii, Bing Xia, Hyung Rae Kim, Chiara Pallara, Jooyoung Lee, Kazunori D. Yamada, Xianjin Xu, Kenichiro Imai, Zhiping Weng, Luigi Cavallo, Tyler M. Borrman, Jianlin Cheng, Marc F. Lensink, Huan-Xiang Zhou, Jilong Li, Gydo C. P. van Zundert, Brian Jiménez-García, Tsukasa Nakamura, Scott E. Mottarella, Sandor Vajda
Publikováno v:
Proteins-Structure, Function and Bioinformatics
Proteins-Structure, Function and Bioinformatics, Wiley, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348 〈10.1002/prot.25007〉
Proteins-Structure, Function and Bioinformatics, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348. ⟨10.1002/prot.25007⟩
Proteins-Structure, Function and Bioinformatics, Wiley, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348. ⟨10.1002/prot.25007⟩
Recercat. Dipósit de la Recerca de Catalunya
instname
Proteins
Proteins: Structure function and bioinformatics, 84(S1), 323. Wiley-Liss Inc.
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Proteins-Structure, Function and Bioinformatics, Wiley, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348 〈10.1002/prot.25007〉
Proteins-Structure, Function and Bioinformatics, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348. ⟨10.1002/prot.25007⟩
Proteins-Structure, Function and Bioinformatics, Wiley, 2016, Special Issue: Eleventh Meeting on the Critical Assessment of Techniques for Protein Structure Prediction, 84 (S1), pp.323-348. ⟨10.1002/prot.25007⟩
Recercat. Dipósit de la Recerca de Catalunya
instname
Proteins
Proteins: Structure function and bioinformatics, 84(S1), 323. Wiley-Liss Inc.
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8102faf768692c2ecf1ed7b49988fca7
https://hal.inria.fr/hal-01309105
https://hal.inria.fr/hal-01309105
Publikováno v:
Journal of Chemical Information and Modeling
Journal of Chemical Information and Modeling, American Chemical Society, 2016, 56 (6), pp.1053-1062. ⟨10.1021/acs.jcim.5b00339⟩
Journal of Chemical Information and Modeling, 2016, 56 (6), pp.1053-1062. ⟨10.1021/acs.jcim.5b00339⟩
Journal of Chemical Information and Modeling, American Chemical Society, 2016, 56 (6), pp.1053-1062. ⟨10.1021/acs.jcim.5b00339⟩
Journal of Chemical Information and Modeling, 2016, 56 (6), pp.1053-1062. ⟨10.1021/acs.jcim.5b00339⟩
International audience; The 2013–2014 CSAR docking exercise was the opportunity to assess the performance of the novel knowledge-based potential we are developing, named Convex-PL. The data used to derive the potential consists only of structural i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b743c0f87c831cd4c34bb0e1e114b26
https://hal.inria.fr/hal-01258022
https://hal.inria.fr/hal-01258022
Publikováno v:
Quarterly Journal of the Royal Meteorological Society
Quarterly Journal of the Royal Meteorological Society, Wiley, 2016, 142 (694), pp.515-528. ⟨10.1002/qj.2676⟩
Quarterly Journal of the Royal Meteorological Society, 2016, 142 (694), pp.515-528. ⟨10.1002/qj.2676⟩
Quarterly Journal of the Royal Meteorological Society, Wiley, 2016, 142 (694), pp.515-528. ⟨10.1002/qj.2676⟩
Quarterly Journal of the Royal Meteorological Society, 2016, 142 (694), pp.515-528. ⟨10.1002/qj.2676⟩
International audience; In order to lower the computational cost of the variational data assimilation process, we investigate the use of multigrid methods to solve the associated optimal control system. On a linear advection equation, we study the im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1c40d4c695a70e07716c5d39232ffd9
https://hal.inria.fr/hal-01246349
https://hal.inria.fr/hal-01246349
Publikováno v:
Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012
Eric Blayo; Marc Bocquet; Emmanuel Cosme; F. Cugliandolo Leticia. Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012, Oxford University Press, pp.576, 2014, Lecture notes of "Les Houches" summer school 2012, 9780198723844. ⟨10.1093/acprof:oso/9780198723844.003.0017⟩
Eric Blayo; Marc Bocquet; Emmanuel Cosme; F. Cugliandolo Leticia. Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012, Oxford University Press, pp.576, 2014, Lecture notes of "Les Houches" summer school 2012, 9780198723844. ⟨10.1093/acprof:oso/9780198723844.003.0017⟩
This chapter looks at the use of multigrid methods and local mesh refinement algorithms in the context of the variational data assimilation method. Firstly, the chapter looks back at basic properties of the traditional variational data assimilation m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ff7fb4ddb9d34250e4a97b4ca4393b
https://hal.inria.fr/hal-01095939
https://hal.inria.fr/hal-01095939