Auflistung Artikel in Fachzeitschriften nach Autor "Rosenstiel, Philip"

2021-04-22Zeitschriftenartikel

Genome-wide analysis of 944 133 individuals provides insights into the etiology of haemorrhoidal disease

Zheng, Tenghao; Ellinghaus, David; Juzenas, Simonas; Cossais, François; Burmeister, Greta; Mayr, Gabriele; Jørgensen, Isabella Friis; Teder-Laving, Maris; Skogholt, Anne Heidi; Chen, Sisi; Strege, Peter R.; Ito, Go; Banasik, Karina; Becker, Thomas; Bokelmann, Frank; Brunak, Søren; Buch, Stephan; Clausnitzer, Hartmut; Datz, Christian; DBDS Consortium; Degenhardt, Frauke; Doniec, Marek; Erikstrup, Christian; Esko, Tõnu; Forster, Michael; Frey, Norbert; Fritsche, Lars G.; Elvestad Gabrielsen, Maiken; Gräßle, Tobias; Gsur, Andrea; Gross, Justus; Hampe, Jochen; Hendricks, Alexander; Hinz, Sebastian; Hveem, Kristian; Jongen, Johannes; Junker, Ralf; Karlsen, Tom Hemming; Hemmrich-Stanisak, Georg; Kruis, Wolfgang; Kupcinskas, Jouzas; Laubert, Tilman; Rosenstiel, Philip C.; Röcken, Christoph; Laudes, Matthias; Leendertz, Fabian H.; Lieb, Wolfgang; Limperger, Verena; Margetis, Nikolaos; Mätz-Rensing, Kerstin; Németh, Christopher Georg; Ness-Jensen, Eivind; Nowak-Göttl, Ulrike; Pandit, Anita; Birger Pedersen, Ole; Peleikis, Hans Günter; Peuker, Kenneth; Rodriguez, Cristina Leal; Rühlemann, Malte Christoph; Schniewind, Bodo; Schulzky, Martin; Skieceviciene, Jurgita; Tepel, Jürgen; Thomas, Laurent; Uellendahl-Werth, Florian; Ullum, Henrik; Vogel, Ilka; Volzke, Henry; von Fersen, Lorenzo; von Schönfels, Witigo; Vanderwerff, Brett; Wilking, Julia; Wittig, Michael; Zeissig, Sebastian; Zobel, Myrko; Zawistowski, Matthew; Vacic, Vladimir; Sazonova, Olga; Noblin, Elizabeth S.; The 23andMe Research Team; Farrugia, Gianrico; Beyder, Arthur; Wedel, Thilo; Kahlke, Volker; Schafmayer, Clemens; D'Amato, Mauro; Franke, Andre

Objective Haemorrhoidal disease (HEM) affects a large and silently suffering fraction of the population but its aetiology, including suspected genetic predisposition, is poorly understood. We report the first genome-wide ...

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 ...