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Swarm Learning for decentralized and confidential clinical machine learning

Autor: Warnat-Herresthal, S. Schultze, H. Shastry, K.L. Manamohan, S. Mukherjee, S. Garg, V. Sarveswara, R. Händler, K. Pickkers, P. Aziz, N.A. Ktena, S. Tran, F. Bitzer, M. Ossowski, S. Casadei, N. Herr, C. Petersheim, D. Behrends, U. Kern, F. Fehlmann, T. Schommers, P. Lehmann, C. Augustin, M. Rybniker, J. Altmüller, J. Mishra, N. Bernardes, J.P. Krämer, B. Bonaguro, L. Schulte-Schrepping, J. De Domenico, E. Siever, C. Kraut, M. Desai, M. Monnet, B. Saridaki, M. Siegel, C.M. Drews, A. Nuesch-Germano, M. Theis, H. Heyckendorf, J. Schreiber, S. Kim-Hellmuth, S. Balfanz, P. Eggermann, T. Boor, P. Hausmann, R. Kuhn, H. Isfort, S. Stingl, J.C. Schmalzing, G. Kuhl, C.K. Röhrig, R. Marx, G. Uhlig, S. Dahl, E. Müller-Wieland, D. Dreher, M. Marx, N. Nattermann, J. Skowasch, D. Kurth, I. Keller, A. Bals, R. Nürnberg, P. Rieß, O. Rosenstiel, P. Netea, M.G. Theis, F. Mukherjee, S. Backes, M. Aschenbrenner, A.C. Ulas, T. Angelov, A. Bartholomäus, A. Becker, A. Bezdan, D. Blumert, C. Bonifacio, E. Bork, P. Boyke, B. Blum, H. Clavel, T. Colome-Tatche, M. Cornberg, M. De La Rosa Velázquez, I.A. Diefenbach, A. Dilthey, A. Fischer, N. Förstner, K. Franzenburg, S. Frick, J.-S. Gabernet, G. Gagneur, J. Ganzenmueller, T. Gauder, M. Geißert, J. Goesmann, A. Göpel, S. Grundhoff, A. Grundmann, H. Hain, T. Hanses, F. Hehr, U. Heimbach, A. Hoeper, M. Horn, F. Hübschmann, D. Hummel, M. Iftner, T. Iftner, A. Illig, T. Janssen, S. Kalinowski, J. Kallies, R. Kehr, B. Keppler, O.T. Klein, C. Knop, M. Kohlbacher, O. Köhrer, K. Korbel, J. Kremsner, P.G. Kühnert, D. Landthaler, M. Li, Y. Ludwig, K.U. Makarewicz, O. Marz, M. McHardy, A.C. Mertes, C. Münchhoff, M. Nahnsen, S. Nöthen, M. Ntoumi, F. Overmann, J. Peter, S. Pfeffer, K. Pink, I. Poetsch, A.R. Protzer, U. Pühler, A. Rajewsky, N. Ralser, M. Reiche, K. Ripke, S. da Rocha, U.N. Saliba, A.-E. Sander, L.E. Sawitzki, B. Scheithauer, S. Schiffer, P. Schmid-Burgk, J. Schneider, W. Schulte, E.-C. Sczyrba, A. Sharaf, M.L. Singh, Y. Sonnabend, M. Stegle, O. Stoye, J. Vehreschild, J. Velavan, T.P. Vogel, J. Volland, S. von Kleist, M. Walker, A. Walter, J. Wieczorek, D. Winkler, S. Ziebuhr, J. Breteler, M.M.B. Giamarellos-Bourboulis, E.J. Kox, M. Becker, M. Cheran, S. Woodacre, M.S. Goh, E.L. Schultze, J.L. COVID-19 Aachen Study (COVAS) Deutsche COVID-19 Omics Initiative (DeCOI)

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2127::2b9a6d09e99524fdf9f7dcb46ca5eafd
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3056276

eDiVA-Classification and prioritization of pathogenic variants for clinical diagnostics

Autor: Bosio M, Drechsel O, Rahman R, Muyas F, Raquel Rabionet Janssen, Bezdan D, Domenech Salgado L, Hor H, Schott JJ, Munell F, Colobran R, Macaya A, Estivill X, Ossowski S

Publikováno v: HUMAN MUTATION
r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
instname
r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
Fundació Sant Joan de Déu

Mendelian diseases have shown to be an and efficient model for connecting genotypes to phenotypes and for elucidating the function of genes. Whole-exome sequencing (WES) accelerated the study of rare Mendelian diseases in families, allowing for direc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1315d60701983a25165028a42bd4f5f7
http://fundanet.fsjd.org/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=17420

The metagenomics and metadesign of the subways and Urban biomes (MetaSUB) international consortium inaugural meeting report

Autor: Afshinnekoo, E, Ahsanuddin, S, Ghedin, E, Read, T, Fraser, C, Dudley, J, Bowler, C, Mason, CE, Chernomoretz, A, Stolovitzky, G, Łabaj, PP, Graf, AB, Darling, A, Burke, C, Noushmehr, H, Dias-Neto, E, Guo, Y, Xie, Z, Lee, PKH, Shi, L, Ruiz-Perez, CA, Zambrano, MM, Siam, R, Ouf, A, Richard, H, Lafontaine, I, Wieler, LH, Semmler, T, Prithiviraj, B, Nedunuri, N, Mehr, S, Banihashemi, K, Lista, F, Anselmo, A, Suzuki, H, Kuroda, M, Yamashita, R, Sato, Y, Kaminuma, E, Aranda, CMA, Martinez, J, Dada, C, Dybwad, M, Oliveira, M, Schuster, S, Siwo, GH, Jang, S, Seo, SC, Hwang, SH, Ossowski, S, Bezdan, D, Chaker, S, Chatziefthimiou, AD, Udekwu, K, Liungdahl, P, Sezerman, U, Meydan, C, Elhaik, E, Gonnet, G, Schriml, LM, Mongodin, E, Huttenhower, C, Gilbert, J, Eisen, J, Hirschberg, D, Hernandez, M, McGrath, K, McGrath, L, Gray, A, Osuolale, O, Segata, N, Fillo, S, Iraola, G, Zhou, Y, Chang, Y, Li, Y, Zhend, Y, Hou, W, Ramirez, A, Cepeda, M, Desnues, C, Rascovan, N, Baron, C, Nagarajan, N, Ercolini, D, Menary, W, Tighe, S, Donia, M, Levy, S, Benito, J, Jones, A, Kasarskis, A, Maritz, J, Jorgensen, E, Neches, R, Livelli, T, Barnetche, JM, Pasolli, E, Greenfield, N, Hasan, N

© 2016 The MetaSUB International Consortium. The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium is a novel, interdisciplinary initiative comprised of experts across many fields, including genomics, dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______363::2e14c2d1ea497d3d0e8ccd347302bc1d
https://hdl.handle.net/10453/62172