FAIR privacy-preserving operation of large genomic variant calling format (VCF) data without download or installation.

Autor: Martins YC; National Laboratory of Scientific Computing, Petrópolis, Brazil., Bhawsar PM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA., Balasubramanian JB; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA., Russ D; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA., Wong WS; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA., Maass W; Saarland University, 66123 Saarbrücken, Germany., Almeida JS; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA.

Publikováno v: AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2024 May 31; Vol. 2024, pp. 65-74. Date of Electronic Publication: 2024 May 31 (Print Publication: 2024).

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

[Digital health applications (DiGA) in the area of tension between progress and criticism : Discussion paper from the "Digital health" specialist group of the German Informatics Society].

Autor: Schlieter H; Forschungsgruppe Digital Health, Fakultät Wirtschaftswissenschaften, Technische Universität Dresden, Dresden, Sachsen, Deutschland., Kählig M; Forschungsgruppe Digital Health, Fakultät Wirtschaftswissenschaften, Technische Universität Dresden, Dresden, Sachsen, Deutschland. maren.kaehlig@tu-dresden.de., Hickmann E; Forschungsgruppe Digital Health, Fakultät Wirtschaftswissenschaften, Technische Universität Dresden, Dresden, Sachsen, Deutschland., Fürstenau D; Department of Business IT, IT University of Copenhagen, Kopenhagen, Dänemark.; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Berlin, Deutschland., Sunyaev A; Institut für Angewandte Informatik und Formale Beschreibungsverfahren, Karlsruher Institut für Technologie, Karlsruhe, Baden-Württemberg, Deutschland., Richter P; Forschungsgruppe Digital Health, Fakultät Wirtschaftswissenschaften, Technische Universität Dresden, Dresden, Sachsen, Deutschland., Breitschwerdt R; Professur für Wirtschaftsinformatik und Medizinische Informatik, Wilhelm Büchner Hochschule, Darmstadt, Hessen, Deutschland., Thielscher C; KompetenzCentrum für Medizinoekonomie, FOM Hochschule, Essen, Nordrhein-Westfalen, Deutschland., Gersch M; Fachbereich Wirtschaftswissenschaften, Freie Universität Berlin, Berlin, Deutschland., Maaß W; Lehrstuhl für Betriebswirtschaftslehre, insbesondere Wirtschaftsinformatik, German Research Center for Artificial Intelligence Universität Saarland, Saarbrücken, Saarland, Deutschland., Reuter-Oppermann M; Faculty of Behavioural, Management and Social Sciences, Center for Healthcare Operations Improvement and Research, University of Twente, Enschede, Niederlande., Wiese L; Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Leader Research Group Bioinformatics, Hannover, Niedersachsen, Deutschland.

Publikováno v: Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz [Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz] 2024 Jan; Vol. 67 (1), pp. 107-114. Date of Electronic Publication: 2023 Dec 12.

PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data.

Autor: Sandoval L; Department of Biomedical Informatics, George Mason University, Fairfax, VA 22030, United States.; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Jafri S; Department of Biomedical Informatics, George Mason University, Fairfax, VA 22030, United States., Balasubramanian JB; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Bhawsar P; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Edelson JL; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Martins Y; Bioinformatics Laboratory, National Laboratory for Scientific Computing, Petropolis 25651, Brazil., Maass W; Saarland University, 66123 Saarbrücken, Germany., Chanock SJ; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Garcia-Closas M; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States., Almeida JS; Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Rockville, MD 20850, United States.

Publikováno v: Bioinformatics advances [Bioinform Adv] 2023 Oct 09; Vol. 3 (1), pp. vbad145. Date of Electronic Publication: 2023 Oct 09 (Print Publication: 2023).

CCN GAC Workshop: Issues with learning in biological recurrent neural networks

Autor: Prince, LY, Boven, E, Eyono, RH, Ghosh, A, Pemberton, J, Scherr, F, Clopath, C, Costa, RP, Maass, W, Richards, BA, Savin, C, Wilmes, KA

This perspective piece came about through the Generative Adversarial Collaboration (GAC) series of workshops organized by the Computational Cognitive Neuroscience (CCN) conference in 2020. We brought together a number of experts from the field of the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1032::9fb04684e3a62e39fce645482488bff7
http://hdl.handle.net/10044/1/88918