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93 results on '"Glatard, T."'

1. Variability in the analysis of a single neuroimaging dataset by many teams

Author

Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M. W. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A. E., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B.B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C. P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Cheng Phui, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka,Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, van ‘t Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Lei Zhang, Zhang, Xu, Zosky, Joshua E., Thomas E. Nichols, Poldrack, Rusell A., Schonberg, Tom, Melero Carrasco, Helena, Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M. W. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A. E., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B.B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C. P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Cheng Phui, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka,Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, van ‘t Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Lei Zhang, Zhang, Xu, Zosky, Joshua E., Thomas E. Nichols, Poldrack, Rusell A., Schonberg, Tom, and Melero Carrasco, Helena

Abstract

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed., Depto. de Psicobiología y Metodología en Ciencias del Comportamiento, Fac. de Psicología, TRUE, pub

Published
2024

3. Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective

Author

Levitis, E, van Praag, CDG, Gau, R, Heunis, S, DuPre, E, Kiar, G, Bottenhorn, KL, Glatard, T, Nikolaidis, A, Whitaker, KJ, Mancini, M, Niso, G, Afyouni, S, Alonso-Ortiz, E, Appelhoff, S, Arnatkeviciute, A, Atay, SM, Auer, T, Baracchini, G, Bayer, JMM, Beauvais, MJS, Bijsterbosch, JD, Bilgin, IP, Bollmann, S, Botvinik-Nezer, R, Bright, MG, Calhoun, VD, Chen, X, Chopra, S, Hu, C-P, Close, TG, Cookson, SL, Craddock, RC, De la Vega, A, De Leener, B, Demeter, D, Di Maio, P, Dickie, EW, Eickhoff, SB, Esteban, O, Finc, K, Frigo, M, Ganesan, S, Ganz, M, Garner, KG, Garza-Villarreal, EA, Gonzalez-Escamilla, G, Goswami, R, Griffiths, JD, Grootswagers, T, Guay, S, Guest, O, Handwerker, DA, Herholz, P, Heuer, K, Huijser, DC, Iacovella, V, Joseph, MJE, Karakuzu, A, Keator, DB, Kobeleva, X, Kumar, M, Laird, AR, Larson-Prior, LJ, Lautarescu, A, Lazari, A, Legarreta, JH, Li, X-Y, Lv, J, Mansour, SL, Meunier, D, Moraczewski, D, Nandi, T, Nastase, SA, Nau, M, Noble, S, Norgaard, M, Obungoloch, J, Oostenveld, R, Orchard, ER, Poldrack, RA, Qiu, A, Raamana, PR, Rokem, A, Rutherford, S, Sharan, M, Shaw, TB, Syeda, WT, Testerman, MM, Toro, R, Valk, SL, Van den Bossche, S, Varoquaux, G, Vasa, F, Veldsman, M, Vohryzek, J, Wagner, AS, Walsh, RJ, White, T, Wong, F-T, Xie, X, Yan, C-G, Yang, Y-F, Yee, Y, Zanitti, GE, Van Gulick, AE, Duff, E, Maumet, C, Levitis, E, van Praag, CDG, Gau, R, Heunis, S, DuPre, E, Kiar, G, Bottenhorn, KL, Glatard, T, Nikolaidis, A, Whitaker, KJ, Mancini, M, Niso, G, Afyouni, S, Alonso-Ortiz, E, Appelhoff, S, Arnatkeviciute, A, Atay, SM, Auer, T, Baracchini, G, Bayer, JMM, Beauvais, MJS, Bijsterbosch, JD, Bilgin, IP, Bollmann, S, Botvinik-Nezer, R, Bright, MG, Calhoun, VD, Chen, X, Chopra, S, Hu, C-P, Close, TG, Cookson, SL, Craddock, RC, De la Vega, A, De Leener, B, Demeter, D, Di Maio, P, Dickie, EW, Eickhoff, SB, Esteban, O, Finc, K, Frigo, M, Ganesan, S, Ganz, M, Garner, KG, Garza-Villarreal, EA, Gonzalez-Escamilla, G, Goswami, R, Griffiths, JD, Grootswagers, T, Guay, S, Guest, O, Handwerker, DA, Herholz, P, Heuer, K, Huijser, DC, Iacovella, V, Joseph, MJE, Karakuzu, A, Keator, DB, Kobeleva, X, Kumar, M, Laird, AR, Larson-Prior, LJ, Lautarescu, A, Lazari, A, Legarreta, JH, Li, X-Y, Lv, J, Mansour, SL, Meunier, D, Moraczewski, D, Nandi, T, Nastase, SA, Nau, M, Noble, S, Norgaard, M, Obungoloch, J, Oostenveld, R, Orchard, ER, Poldrack, RA, Qiu, A, Raamana, PR, Rokem, A, Rutherford, S, Sharan, M, Shaw, TB, Syeda, WT, Testerman, MM, Toro, R, Valk, SL, Van den Bossche, S, Varoquaux, G, Vasa, F, Veldsman, M, Vohryzek, J, Wagner, AS, Walsh, RJ, White, T, Wong, F-T, Xie, X, Yan, C-G, Yang, Y-F, Yee, Y, Zanitti, GE, Van Gulick, AE, Duff, E, and Maumet, C

Abstract

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Published
2021

4. Grid-enabling medical image analysis

Author

Germain, C., Breton, V., Clarysse, P., Gaudeau, Y., Glatard, T., Jeannot, E., Legré, Y, Loomis, C., Magnin, I., Montagnat, J., Moureaux, J. -M., Osorio, A., Pennec, X., and Texier, R.

Published
2005
Full Text
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5. Sharing brain mapping statistical results with the neuroimaging data model.

Author

Maumet, C, Auer, T, Bowring, A, Chen, G, Das, S, Flandin, G, Ghosh, S, Glatard, T, Gorgolewski, KJ, Helmer, KG, Jenkinson, M, Keator, DB, Nichols, BN, Poline, J-B, Reynolds, R, Sochat, V, Turner, J, Nichols, TE, Maumet, C, Auer, T, Bowring, A, Chen, G, Das, S, Flandin, G, Ghosh, S, Glatard, T, Gorgolewski, KJ, Helmer, KG, Jenkinson, M, Keator, DB, Nichols, BN, Poline, J-B, Reynolds, R, Sochat, V, Turner, J, and Nichols, TE

Abstract

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html.

Published
2016

6. Global Initiative for Sentinel e-Health Network on Grid (GINSENG), Medical data integration and semantic developments for epidemiology

Author

Cipiere, S., Ereteo, G., Alban Gaignard, Boujelben N., Gaspard, S., Vincent Breton, Cervenansky, F., Hill, David R. C., Glatard, T., Manset, D., Montagnat, J., And Maigne, L. Revillard J., Web-Instrumented Man-Machine Interactions, Communities and Semantics (WIMMICS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Université Nice Sophia Antipolis (... - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS)

Subjects
[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2014

7. Image Based Modelling

Author

Frangi, A., Friboulet, Denis, Ayache, Nicholas, Delingette, H., Glatard, T., Hoogendoorn, C., Humbert, L., Lekadir, K., Larrabide, I., Martelli, Y., Peyrin, F., Planes, X., Sermesant, Maxime, Villa-Uriol, M.C., Whitmarsh, T., Atkinson, D., Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra [Barcelona] (UPF), Department of Mechanical Engineering [Sheffield], University of Sheffield [Sheffield], Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Analysis and Simulation of Biomedical Images (ASCLEPIOS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Imagerie Tomographique et Radiothérapie, Center for medical imaging, University College of London [London] (UCL), Peter Coveney, Vanessa Diaz, Peter Hunter, Marco Viceconti, Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2014

8. Design of an ontology for the annotation of object models used for medical image simulation

Author

Gibaud , B., Forestier , G., Benoit-Cattin , B., Cervenansky , F., Clarysse , P., Friboulet , D., Gaignard , A., Hugonnard , P., Lartizien , C., Liebgott , H., Montagnat , J., Tabary , J., Glatard , T., Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Modélisation, Intelligence, Processus et Système (MIPS), Ecole Nationale Supérieure d'Ingénieur Sud Alsace-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-IUT de Colmar-IUT de Mulhouse, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service Informatique et développements, Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS, Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Imagerie Ultrasonore, Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Modélisation, Intelligence, Processus et Système ( MIPS ), Université de Haute-Alsace (UHA) Mulhouse - Colmar ( Université de Haute-Alsace (UHA) ) -Ecole Nationale Supérieure d'Ingénieur Sud Alsace, 2 - Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), 1 - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales ( MOTIVATE ), Scalable and Pervasive softwARe and Knowledge Systems ( SPARKS ), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis ( I3S ), Université Nice Sophia Antipolis ( UNS ), Université Côte d'Azur ( UCA ) -Université Côte d'Azur ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Nice Sophia Antipolis ( UNS ), Université Côte d'Azur ( UCA ) -Université Côte d'Azur ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ) -Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis ( I3S ), Université Côte d'Azur ( UCA ) -Université Côte d'Azur ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Electronique et des Technologies de l'Information ( CEA-LETI ), Université Grenoble Alpes [Saint Martin d'Hères]-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), 3 - Imagerie Ultrasonore, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA)), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)

Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2012

9. HealthGrid 2012

Author

Glatard, T., Olabarriaga, S., Solomonides, T., Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), CCRI, and NorthShore University HealthSystem

Subjects
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2012

10. HealthGrid Applications and Technologies meet Science Gateways for Life Sciences, proceedings of HealthGrid 2012

Author

Gesing, S., Glatard, T., Krüger, J., Delgado Olabarriaga, S., Solomonides, T., Silverstein, J.C., Montagnat, Johan, Gaignard, A., Krefting, D., Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Amsterdam [Amsterdam] (UvA), CCRI, NorthShore University HealthSystem, Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS, Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), University of Applied Sciences of Berlin, and Technische Universität Berlin (TU)

Subjects
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

International audience; The integration of grid, cloud and other e-infrastructures into the fields of biology, bioinformatics, biomedicine, and healthcare are crucial if optimum use is to be made of the latest high-performance and distributed computer technology in these areas. Science gateways are concerned with offering intuitive graphical user interfaces to applications, data, and tools on distributed computing infrastructures. This book presents the joint proceedings of the Tenth HealthGrid Conference and the Fourth International Workshop on Science Gateways for Life Sciences (IWSG-Life), held in Amsterdam, the Netherlands in May 2012. The HealthGrid conference promotes the exchange and debate of ideas, technologies and solutions likely to promote the integration of grids into biomedical research and health in the broadest sense. The IWSG-Life workshop series is a forum that brings together scientists from the field of life sciences, bioinformatics, and computer science to advance computational biology and chemistry in the context of science gateways. These events have been jointly organized to maximize the benefit from synergies and stimulate the forging of further links in joint research areas. HealthGrid Applications and Technologies Meet Science Gateways for Life Sciences is divided into three parts. Part I includes contributions accepted to the HealthGrid conference; Part II contains the papers about various aspects of the development and usage of science gateways for life sciences. The joint session is recorded in Part III, and addresses the topic of science gateways for biomedical research. This book will provide insights and new perspectives for all those involved in the research and use of infrastructures and technology for healthcare and life sciences.

Published
2012

11. Integrated support for neuroscience research: from study design to publication

Author

Shahand, S., Caan, M.W.A., van Kampen, A.H.C., Olabarriaga, S.D., Gesing, S., Glatard, T., Krüger, J., Delgado Olabarriaga, S., Solomonides, T., Silverstein, J.C., Montagnat, J., Gaignard, A., Krefting, D., Biosystems Data Analysis (SILS, FNWI), and Faculteit der Geneeskunde

Abstract

Computational neuroscience is a new field of research in which neurodegenerative diseases are studied with the aid of new imaging techniques and computation facilities. Researchers with different expertise collaborate in these studies. A study requires scalable computational and storage capacity and information management facilities to succeed. Many virtual laboratories are proposed and developed to facilitate these studies, however most of them cover only the parts related to the computational data processing. In this paper we describe and analyse the phases of the computational neuroscience studies including the actors, the tasks they perform, and the characteristics of each phase. Based on these we identify the required properties and functionalities of a virtual laboratory that supports the actors and their tasks throughout the complete study.

Published
2012

12. Infrastructure DIRAC pour les Communautés Pluridisciplinaires

Author

Tsaregorodtsev, A., Hamar, V., Sapunov, M., Glatard, T., Camarasu-Pop, S., Ferreira da Silva, R., Girard, Pascal, Gay, P., Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service Informatique et développements, Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Sciences et Technologies - Bordeaux 1, Sciencesconf.org, CCSD, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Sciences et Technologies - Bordeaux 1 (UB), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
grilles des calcul, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], DIRAC, systemes de calcul distribués, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

Le projet DIRAC fournit un cadre logiciel pour créer des systèmes de calcul distribués pour différentes communautés d'utilisateurs. DIRAC supporte plusieurs communautés (organisations virtuelles) avec un seule installation. Le portail Web, le système d'ordonnancement des tâches avec les agents-pilotes, le système de récupération des échecs et d'autres propriétés du logiciel DIRAC servent à aider les utilisateurs non-experts a à utiliser facilement les ressources de calcul de la grille.; International audience; Infrastructure DIRAC pour les Communautés Pluridisciplinaires

Published
2011

13. Workflow Integration in VL-e Medical

Author

Glatard, T., Boulebiar, K., Olabarriaga, S. D., Puuronen, Seppo, Pechenizkiy, Mykola, Tsymbal, Alexey, Lee, Dah-Jye, and Epidemiology and Data Science

Subjects
Computer science, business.industry, Data management, computer.software_genre, Virtual file system, Workflow, Grid computing, Middleware, Medical software, Operating system, Software architecture, business, computer, Workflow management system
Abstract

This paper presents the integration of a workflow management system into the VL-e medical software architecture. Workflows are designed with the Taverna workbench, and then executed with the MOTEUR engine on the EGEE grid through the VBrowser, which is the basic front-end for grid-enabled applications in the VL-e medical project. Data management is handled by the virtual file system of the VL-e toolkit. The resulting system provides a high-level interface to execute grid applications.

Published
2011

14. Optimization of Mean-Shift scale parameters on the EGEE grid

Author

Li, T, Camarasu-Pop, Sorina, Glatard, T, Grenier, T, Benoit-Cattin, H., Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Images et Modèles, categₛt2i, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2010

15. A comparison between ARC and gLite for medical image processing on Grids

Author

Glatard, T, Zhou, X. ., Camarasu-Pop, Sorina, Smirnova, O. ., Muller, H. ., Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Service Informatique et développements

Subjects
reseau_international, Images et Modèles, Suède, categₛt2i, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Suisse, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2009

16. User friendly management of workflow results: from provenance information to grid logical file names

Author

Glatard, T., Olabarriaga, S. D., van Engelen, Robert, Govindaraju, Madhu, Cafaro, Massimo, and Epidemiology and Data Science

Subjects
Workflow, Database, Distributed database, Grid computing, Windows Workflow Foundation, Computer science, computer.software_genre, Workflow engine, computer, Workflow management system, Directory structure, Workflow technology
Abstract

Grid workflows can produce thousands of results that should be properly organised to enable further analysis. Typically results are stored on locations hard-coded in the workflow or in the components, limiting reusability. In this paper we present an approach to (re)organise the output files generated by a grid workflow in a distributed storage environment. We propose to perform a post-mortem mapping of workflow results into a directory structure. This mapping is based on data provenance information and exploits grid catalog features, namely logical file names, to avoid data replication. By defining different mappings, users can generate their own semantic view of results generated during a workflow execution, which fosters user-friendliness, whereas preserving workflow reusability. An implementation on the Virtual Resource Browser (VBrowser) framework is detailed and evaluated on neuroimaging workflows. Results show that the complex directory structure of an image analysis application cane properly generated by our system. An initial performance evaluation of the mapping resolution and directory structure creation indicates that this approach provides a practical, simple, yet powerful solution to an important roadblock for the adoption of workflows to implement complex image analysis pipelines.

Published
2008

17. iBRAIN2: Automated analysis and data handling for RNAi screens

Author

Gesing, Sandra, Glatard, Tristan, Olabarriaga, Silvia Delgado, Solomonides, Tony, Silverstein, Jonathan C, Montagnat, Johan, Gaignard, Alban, Krefting, Dagmar, Gesing, S ( Sandra ), Glatard, T ( Tristan ), Olabarriaga, S D ( Silvia Delgado ), Solomonides, T ( Tony ), Silverstein, J C ( Jonathan C ), Montagnat, J ( Johan ), Gaignard, A ( Alban ), Krefting, D ( Dagmar ), Rouilly, Vincent, Pujadas, Eva, Hullár, Béla, Balázs, Csabas, Kunszt, Peter, Podvinec, Michael, Gesing, Sandra, Glatard, Tristan, Olabarriaga, Silvia Delgado, Solomonides, Tony, Silverstein, Jonathan C, Montagnat, Johan, Gaignard, Alban, Krefting, Dagmar, Gesing, S ( Sandra ), Glatard, T ( Tristan ), Olabarriaga, S D ( Silvia Delgado ), Solomonides, T ( Tony ), Silverstein, J C ( Jonathan C ), Montagnat, J ( Johan ), Gaignard, A ( Alban ), Krefting, D ( Dagmar ), Rouilly, Vincent, Pujadas, Eva, Hullár, Béla, Balázs, Csabas, Kunszt, Peter, and Podvinec, Michael

Abstract

We report on the implementation of a software suite dedicated to the management and analysis of large scale RNAi High Content Screening (HCS). We describe the requirements identified amongst our different users, the supported data flow, and the implemented software. Our system is already supporting productively three different laboratories operating in distinct IT infrastructures. The system was already used to analyze hundreds of RNAi HCS plates.

Published
2012

18. gcodeml: A Grid-enabled Tool for Detecting Positive Selection in Biological Evolution

Author

Glatard, T (ed.), Silverstein, J (ed.), Moretti, S., Murri, R., Maffioletti, S., Kuzniar, A., Castella, B, Salamin, N., Robinson-Rechavi, M., Stockinger, H., Glatard, T (ed.), Silverstein, J (ed.), Moretti, S., Murri, R., Maffioletti, S., Kuzniar, A., Castella, B, Salamin, N., Robinson-Rechavi, M., and Stockinger, H.

Abstract

One of the important questions in biological evolution is to know if certain changes along protein coding genes have contributed to the adaptation of species. This problem is known to be biologically complex and computationally very expensive. It, therefore, requires efficient Grid or cluster solutions to overcome the computational challenge. We have developed a Grid-enabled tool (gcodeml) that relies on the PAML (codeml) package to help analyse large phylogenetic datasets on both Grids and computational clusters. Although we report on results for gcodeml, our approach is applicable and customisable to related problems in biology or other scientific domains.

Published
2012

20. A Virtual Imaging Platform for Multi-Modality Medical Image Simulation

Author

Glatard, T., primary, Lartizien, C., additional, Gibaud, B., additional, Ferreira da Silva, Rafael, additional, Forestier, G., additional, Cervenansky, F., additional, Alessandrini, M., additional, Benoit-Cattin, H., additional, Bernard, O., additional, Camarasu-Pop, S., additional, Cerezo, N., additional, Clarysse, P., additional, Gaignard, A., additional, Hugonnard, P., additional, Liebgott, H., additional, Marache, S., additional, Marion, A., additional, Montagnat, J., additional, Tabary, J., additional, and Friboulet, D., additional

Published
2013
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38. 2012 Activity Report of the Regional Research Programme on Hadrontherapy for the ETOILE Center

Author

Alphonse, G., Ardail, D., Armandy, E., Bajard, M., Balosso, J., H Baron, M., Battiston-Montagne, P., Bertrand, G., Beuve, M., Marie-Claude Biston, Blanchard, G., Bouhadiba, O., Boutin, B., Cajavec-Bernard, B., Chandez, F., A Chanrion, M., Chollier, L., Constanzo, J., Cunha, M., Djamel Dabli, Dahoumane, M., Dauvergne, D., Rydt, M., Dedes, G., Deng, S., Ducimetière, F., Fallavier, M., Fayet, Y., Ferrandon, S., Force, P., Freud, N., Gagnon, C., Ganne, C., Gautier, M., Gilormini, M., Glatard, T., Hu, Y., Insa, C., Jaillet, F., Baptiste Joly, Krimmer, J., Hamid Ladjal, Lambert, D., Loïc Lestand, Letang, J. M., L Ley, J., Magné, N., Malesys, C., Martin, F., Mathez, H., Voichita Maxim, Moncharmont, C., Gerard Montarou, M Moreau, J., Pequegnot, L., Patin, S., Pauna, N., Pinto, M., Pommier, P., Poncet, D., Pop-Camarasu, S., Prost, R., Ray, C., Isabelle Ray-Coquard, Reithinger, V., Remillieux, J., Ribba, S., H Richard, M., Rit, S., Rodriguez-Lafrasse, C., Roellinghoff, F., Royer, L., Sarrut, D., Shariat, B., Testa, E., E Vert, P., Vial, L., Vogin, G., Florence Zara, Zoccarato, Y., Ciblage thérapeutique en Oncologie ( EA3738 ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon, Institut de Physique Nucléaire de Lyon ( IPNL ), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Université Joseph Fourier - Grenoble 1 ( UJF ), Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC ( CEF2P / CARCINO ), Université Bourgogne Franche-Comté ( UBFC ) -Université de Franche-Comté ( UFC ) -Centre Hospitalier Régional Universitaire [Besançon] ( CHRU Besançon ), Centre Léon Bérard [Lyon], Laboratoire de Physique Corpusculaire - Clermont-Ferrand ( LPC ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Université de Lyon, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé ( CREATIS ), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Université Jean Moulin - Lyon III, 4 - Imagerie Tomographique et Radiothérapie, Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Hospices Civils de Lyon ( HCL ) -Université Jean Monnet [Saint-Étienne] ( UJM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Claude Bernard Lyon 1 ( UCBL ), Pôle Information Médicale Evaluation Recherche ( IMER ), Hospices Civils de Lyon ( HCL ), 2 - Images et Modèles, Laboratoire Biostatistique-Santé ( LBS ), Université de Lyon-Université de Lyon-Hospices Civils de Lyon ( HCL ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), OMéRRIC network, GCS ETOILE, Service Informatique et développements, Numerical Medicine ( NUMED ), Unité de Mathématiques Pures et Appliquées ( UMPA-ENSL ), École normale supérieure - Lyon ( ENS Lyon ) -Centre National de la Recherche Scientifique ( CNRS ) -École normale supérieure - Lyon ( ENS Lyon ) -Centre National de la Recherche Scientifique ( CNRS ) -Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Institut de Cancérologie Lucien Neuwirth, CHU Saint-Etienne, Centre Etoile, Université Lyon 1 - Claude Bernard, Ciblage thérapeutique en Oncologie (EA3738), Université Claude Bernard Lyon 1 (UCBL), Institut de Physique Nucléaire de Lyon (IPNL), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Université Joseph Fourier - Grenoble 1 (UJF), Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC (EA 3181) (CEF2P / CARCINO), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Laboratoire de Physique Corpusculaire - Clermont-Ferrand (LPC), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Jean Moulin - Lyon 3 (UJML), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Pôle Information Médicale Evaluation Recherche (IMER), Hospices Civils de Lyon (HCL), Images et Modèles, Biostatistiques santé, Département biostatistiques et modélisation pour la santé et l'environnement [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2), Simulation, Analyse et Animation pour la Réalité Augmentée (SAARA), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Numerical Medicine (NUMED), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Unité de Mathématiques Pures et Appliquées (UMPA-ENSL), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC (UR 3181) (CEF2P / CARCINO), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Unité de Mathématiques Pures et Appliquées (UMPA-ENSL), École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)

Subjects
[ PHYS.PHYS.PHYS-MED-PH ] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], [SDV.CAN]Life Sciences [q-bio]/Cancer, [ SDV.CAN ] Life Sciences [q-bio]/Cancer
Abstract

2012 is the penultimate year of financial support by the CPER 2007-2013 for ETOILE's research program, sustained by the PRRH at the University Claude Bernard. As with each edition we make the annual review of the research in this group, so active for over 12 years now. Over the difficulties in the decision-making process for the implementation of the ETOILE Center, towards which all our efforts are focussed, some "themes" (work packages) were strengthened, others have progressed, or have been dropped. This is the case of the eighth theme (technological developments), centered around the technology for rotative beam distribution heads (gantries) and, after being synchronized with the developments of ULICE's WP6, remained so by ceasing its activities, coinciding also with the retirement of its historic leader at IPNL, Marcel Bajard. Topic number 5 ("In silico simulations") has suffered the departure of its leader, Benjamin Ribba, although the work has still been provided by Branka Bernard, a former postdoctoral fellow in Lyon Sud, and now back home in Croatia, still in contract with UCBL for the ULICE project. Aside from these two issues (and the fact that the theme "Medico-economical simulations" is now directly linked to the first one ("Medical Project"), the rest of the teams are growing, as evidenced by the publication statistics at the beginning of this report. This is obviously due to the financial support of our always faithful regional institutions, but also to the synergy that the previous years, the European projects, the arrival of the PRIMES LabEx, and the national France Hadron infrastructure have managed to impulse. The Rhone-Alpes hadron team, which naturally includes the researchers of LPC at Clermont, should also see its influence result in a strong presence in France Hadron's regional node, which is being organized. The future of this regional research is not yet fully guaranteed, especially in the still uncertain context of ETOILE, but the tracks are beginning to emerge to allow past and present efforts translate into a long future that we all want to see established. Each of the researchers in PRRH is aware that 2013 will be (and already is) the year of great challenge : for ETOILE, for the PRRH, for hadron therapy in France, for French hadrontherapy in Europe (after the opening and beginning of treatments in the German [HIT Heidelberg, Marburg], Italian [CNAO, Pavia] and Austrian [MedAustron, Wien Neuerstadt]) centers. Let us meet again in early 2014 for a comprehensive review of the past and a perspective for the future ...

39. Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

Author

Glatard, T., Roura, E., Vukusic, S., Khademi, A., Mahbod, A., Dojat, M., Wang, C., Santos, W.P., Doyle, S., Malpica, N., McKinley, R., Valverde, S., Tourdias, T., Commowick, O., Leray, F., Sweeney, E., Girard, P., Santos, M.M., Cabezas, M., Cervenansky, F., Kain, M., Guttmann, C., Styner, M., Ferré, J.-C., Vera-Olmos, F.J., Kerbrat, A., Edan, G., Bloch, I., Wagner, F., Tomas-Fernandez, X., Simon, M., Knight, J., Warfield, S.K., Lladó, X., Muschelli, J., Améli, R., Beaumont, J., Cotton, F., Forbes, F., Pop, S.C., Istace, A., Laurent, B., Barillot, C., Urien, H., and Silva-Filho, A.G.

Subjects
13. Climate action
Abstract

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.

44. gcodeml: A Grid-enabled Tool for Detecting Positive Selection in Biological Evolution

Author

Moretti, S., Murri, R., Maffioletti, S., Kuzniar, A., Castella, B, Salamin, N., Robinson-Rechavi, M., Stockinger, H., Glatard, T (ed.), and Silverstein, J (ed.)

Subjects
ComputingMethodologies_GENERAL
Abstract

One of the important questions in biological evolution is to know if certain changes along protein coding genes have contributed to the adaptation of species. This problem is known to be biologically complex and computationally very expensive. It, therefore, requires efficient Grid or cluster solutions to overcome the computational challenge. We have developed a Grid-enabled tool (gcodeml) that relies on the PAML (codeml) package to help analyse large phylogenetic datasets on both Grids and computational clusters. Although we report on results for gcodeml, our approach is applicable and customisable to related problems in biology or other scientific domains.

Published
2012

45. Why experimental variation in neuroimaging should be embraced.

Author

Kiar G, Mumford JA, Xu T, Vogelstein JT, Glatard T, and Milham MP

Subjects
Humans, Reproducibility of Results, Magnetic Resonance Imaging methods, Research Design, Neuroimaging methods, Brain diagnostic imaging
Abstract

In a perfect world, scientists would develop analyses that are guaranteed to reveal the ground truth of a research question. In reality, there are countless viable workflows that produce distinct, often conflicting, results. Although reproducibility places a necessary bound on the validity of results, it is not sufficient for claiming underlying validity, eventual utility, or generalizability. In this work we focus on how embracing variability in data analysis can improve the generalizability of results. We contextualize how design decisions in brain imaging can be made to capture variation, highlight examples, and discuss how variability capture may improve the quality of results., (© 2024. The Author(s).)

Published
2024
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46. Registered report: Age-preserved semantic memory and the CRUNCH effect manifested as differential semantic control networks: An fMRI study.

Author

Haitas N, Dubuc J, Massé-Leblanc C, Chamberland V, Amiri M, Glatard T, Wilson M, Joanette Y, and Steffener J

Subjects
Humans, Adult, Middle Aged, Aged, Male, Female, Young Adult, Brain Mapping, Nerve Net physiology, Nerve Net diagnostic imaging, Brain physiology, Brain diagnostic imaging, Pre-Registration Publication, Magnetic Resonance Imaging, Semantics, Aging physiology, Memory physiology, Reaction Time physiology
Abstract

Semantic memory representations are generally well maintained in aging, whereas semantic control is thought to be more affected. To explain this phenomenon, this study tested the predictions of the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), focusing on task demands in aging as a possible framework. The CRUNCH effect would manifest itself in semantic tasks through a compensatory increase in neural activation in semantic control network regions but only up to a certain threshold of task demands. This study compares 39 younger (20-35 years old) with 39 older participants (60-75 years old) in a triad-based semantic judgment task performed in an fMRI scanner while manipulating task demand levels (low versus high) through semantic distance. In line with the CRUNCH predictions, differences in neurofunctional activation and behavioral performance (accuracy and response times) were expected in younger versus older participants in the low- versus high-demand conditions, which should be manifested in semantic control Regions of Interest (ROIs). Our older participants had intact behavioral performance, as proposed in the literature for semantic memory tasks (maintained accuracy and slower response times (RTs)). Age-invariant behavioral performance in the older group compared to the younger one is necessary to test the CRUNCH predictions. The older adults were also characterized by high cognitive reserve, as our neuropsychological tests showed. Our behavioral results confirmed that our task successfully manipulated task demands: error rates, RTs and perceived difficulty increased with increasing task demands in both age groups. We did not find an interaction between age group and task demand, or a statistically significant difference in activation between the low- and high-demand conditions for either RTs or accuracy. As for brain activation, we did not find the expected age group by task demand interaction, or a significant main effect of task demand. Overall, our results are compatible with some neural activation in the semantic network and the semantic control network, largely in frontotemporoparietal regions. ROI analyses demonstrated significant effects (but no interactions) of task demand in the left and right inferior frontal gyrus, the left posterior middle temporal gyrus, the posterior inferior temporal gyrus and the prefrontal gyrus. Overall, our test did not confirm the CRUNCH predictions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Haitas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2024
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47. Longitudinal brain structure changes in Parkinson's disease: A replication study.

Author

Sokołowski A, Bhagwat N, Chatelain Y, Dugré M, Hanganu A, Monchi O, McPherson B, Wang M, Poline JB, Sharp M, and Glatard T

Subjects
Humans, Cerebral Cortex pathology, Cerebral Cortical Thinning pathology, Reproducibility of Results, Brain diagnostic imaging, Brain pathology, Magnetic Resonance Imaging, Biomarkers, Parkinson Disease pathology, Cognitive Dysfunction pathology
Abstract

Context: An existing major challenge in Parkinson's disease (PD) research is the identification of biomarkers of disease progression. While magnetic resonance imaging is a potential source of PD biomarkers, none of the magnetic resonance imaging measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations., Objective: This study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinson's Progression Markers Initiative (PPMI)., Methods: Using 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between structural changes and cognitive decline. We compared our findings to the results in the original study., Results: (1) Similarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance., Conclusion: Despite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data is added to PPMI., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sokołowski et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2024
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48. Numerical stability of DeepGOPlus inference.

Author

Gonzalez Pepe I, Chatelain Y, Kiar G, and Glatard T

Subjects
Reproducibility of Results, Amino Acid Sequence, Monte Carlo Method, Neural Networks, Computer, Proteins
Abstract

Convolutional neural networks (CNNs) are currently among the most widely-used deep neural network (DNN) architectures available and achieve state-of-the-art performance for many problems. Originally applied to computer vision tasks, CNNs work well with any data with a spatial relationship, besides images, and have been applied to different fields. However, recent works have highlighted numerical stability challenges in DNNs, which also relates to their known sensitivity to noise injection. These challenges can jeopardise their performance and reliability. This paper investigates DeepGOPlus, a CNN that predicts protein function. DeepGOPlus has achieved state-of-the-art performance and can successfully take advantage and annotate the abounding protein sequences emerging in proteomics. We determine the numerical stability of the model's inference stage by quantifying the numerical uncertainty resulting from perturbations of the underlying floating-point data. In addition, we explore the opportunity to use reduced-precision floating point formats for DeepGOPlus inference, to reduce memory consumption and latency. This is achieved by instrumenting DeepGOPlus' execution using Monte Carlo Arithmetic, a technique that experimentally quantifies floating point operation errors and VPREC, a tool that emulates results with customizable floating point precision formats. Focus is placed on the inference stage as it is the primary deliverable of the DeepGOPlus model, widely applicable across different environments. All in all, our results show that although the DeepGOPlus CNN is very stable numerically, it can only be selectively implemented with lower-precision floating-point formats. We conclude that predictions obtained from the pre-trained DeepGOPlus model are very reliable numerically, and use existing floating-point formats efficiently., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gonzalez Pepe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2024
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49. Data and Tools Integration in the Canadian Open Neuroscience Platform.

Author

Poline JB, Das S, Glatard T, Madjar C, Dickie EW, Lecours X, Beaudry T, Beck N, Behan B, Brown ST, Bujold D, Beauvais M, Caron B, Czech C, Dharsee M, Dugré M, Evans K, Gee T, Ippoliti G, Kiar G, Knoppers BM, Kuehn T, Le D, Lo D, Mazaheri M, MacFarlane D, Muja N, O'Brien EA, O'Callaghan L, Paiva S, Park P, Quesnel D, Rabelais H, Rioux P, Legault M, Tremblay-Mercier J, Rotenberg D, Stone J, Strauss T, Zaytseva K, Zhou J, Duchesne S, Khan AR, Hill S, and Evans AC

Subjects
Canada, Information Dissemination, Databases, Factual, Software
Abstract

We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community's need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates datasets originating from a number of already existing platforms or databases through DataLad, a file level data integrity and access layer. The portal is also an entry point for searching and accessing a large number of standardized and containerized software and links to a computing infrastructure. It leverages community standards to help document and facilitate reuse of both datasets and tools, and already shows a growing community adoption giving access to more than 60 neuroscience datasets and over 70 tools. The CONP portal demonstrates the feasibility and offers a model of a distributed data and tool management system across 17 institutions throughout Canada., (© 2023. The Author(s).)

Published
2023
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50. Play the Pain: A Digital Strategy for Play-Oriented Research and Action.

Author

Khalili-Mahani N, Holowka E, Woods S, Khaled R, Roy M, Lashley M, Glatard T, Timm-Bottos J, Dahan A, Niesters M, Hovey RB, Simon B, and Kirmayer LJ

Abstract

The value of understanding patients' illness experience and social contexts for advancing medicine and clinical care is widely acknowledged. However, methodologies for rigorous and inclusive data gathering and integrative analysis of biomedical, cultural, and social factors are limited. In this paper, we propose a digital strategy for large-scale qualitative health research, using play (as a state of being, a communication mode or context, and a set of imaginative, expressive, and game-like activities) as a research method for recursive learning and action planning. Our proposal builds on Gregory Bateson's cybernetic approach to knowledge production. Using chronic pain as an example, we show how pragmatic, structural and cultural constraints that define the relationship of patients to the healthcare system can give rise to conflicted messaging that impedes inclusive health research. We then review existing literature to illustrate how different types of play including games, chatbots, virtual worlds, and creative art making can contribute to research in chronic pain. Inspired by Frederick Steier's application of Bateson's theory to designing a science museum, we propose DiSPORA (Digital Strategy for Play-Oriented Research and Action), a virtual citizen science laboratory which provides a framework for delivering health information, tools for play-based experimentation, and data collection capacity, but is flexible in allowing participants to choose the mode and the extent of their interaction. Combined with other data management platforms used in epidemiological studies of neuropsychiatric illness, DiSPORA offers a tool for large-scale qualitative research, digital phenotyping, and advancing personalized medicine., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Khalili-Mahani, Holowka, Woods, Khaled, Roy, Lashley, Glatard, Timm-Bottos, Dahan, Niesters, Hovey, Simon and Kirmayer.)

Published
2021
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