Year: 2025
Type: article
Source: Nature Biotechnology
Authors: Sebastian Lobentanzer, Shaohong Feng, Noah Bruderer, Andreas Maier, Adrián G. Díaz, Amy Strange, Anis Ismail, Anton Kulaga, Aurelien Dugourd, Barbara Zdrazil, Bastien Chassagnol, Cyril Pommier, Daniele Lucarelli, Ellen M. McDonagh, Emma Verkinderen, Fernando M. Delgado-Chaves, Georg Fuellen, Hannah Sonntag, Jonatan Menger, Lionel Christiaen, Ludwig Geistlinger, Luna Zacharias Zetsche, Marlis Engelke, Megan McNutt, Melissa Harrison, Melissa Hizli, Nikolai Usanov, Patrick Baracho, Sebastian Beier, Stefan Boeing, Taru A. Muranen, Trang T. Le, Valeriia Dragan, Xiao-Ran Zhou, Yasmin Nielsen-Tehranchian, Yuyao Song, Cankun Wang, Jan Baumbach, Jorge Abreu-Vicente, Nils Krehl, Qin Ma, Thomas Lemberger, Julio Saez-Rodriguez
Institutions: European Bioinformatics Institute, Heidelberg University, University Hospital Heidelberg, Open Targets, The Ohio State University, University of Bergen, Universität Hamburg, Vrije Universiteit Brussel, The Francis Crick Institute, KU Leuven, University of Rostock, Sorbonne Université, Université Paris-Saclay, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Helmholtz Munich, Institute of Computational Biology, Technical University of Munich, Université Libre de Bruxelles, Universitätsmedizin Rostock, European Molecular Biology Organization, University of Freiburg, Harvard University, Heilbronn University, Forschungszentrum Jülich, University of Helsinki, Bristol-Myers Squibb (United States), University of Southern Denmark
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G1518561650, G2467559869, G434337789, Precision drug REPurpOsing For EUrope and the world, EAGER: IIBR Informatics: A reinforced imputation framework for accurate gene expression recovery from single-cell RNA-seq data, Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer, G9000155714, SCH: Graph-based Spatial Transcriptomics Computational Methods in Kidney Diseases, TriState SenNET (Lung and Heart) Tissue Map and Atlas consortium
OpenAlex ID: W4406706905