Probe set selection for targeted spatial transcriptomics.

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Title: Probe set selection for targeted spatial transcriptomics.
Authors: Kuemmerle LB; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; Institute for Tissue Engineering and Regenerative Medicine, Helmholtz Zentrum München, Neuherberg, Germany.; School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany., Luecken MD; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; Institute of Lung Health & Immunity, Helmholtz Munich, Member of the German Center for Lung Research (DZL), Munich, Germany.; German Center for Lung Research (DZL), Gießen, Germany., Firsova AB; SciLifeLab and Department of Molecular Biosciences, Stockholm University, Stockholm, Sweden., Barros de Andrade E Sousa L; Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany., Straßer L; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany., Mekki II; Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany., Campi F; Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany., Heumos L; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.; Institute of Lung Biology and Disease and Comprehensive Pneumology Center, Helmholtz Zentrum München, German Center for Lung Research (DZL), Munich, Germany., Shulman M; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany., Beliaeva V; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany., Hediyeh-Zadeh S; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany., Schaar AC; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.; Munich Center for Machine Learning, Technical University of Munich, Munich, Germany., Mahbubani KT; Department of Surgery, University of Cambridge and Cambridge NIHR Biomedical Research Centre, Cambridge, UK., Sountoulidis A; SciLifeLab and Department of Molecular Biosciences, Stockholm University, Stockholm, Sweden., Balassa T; Synthetic and Systems Biology Unit, Biological Research Centre, Eötvös Loránd Research Network, Szeged, Hungary., Kovacs F; Single-Cell Technologies Ltd, Szeged, Hungary., Horvath P; Synthetic and Systems Biology Unit, Biological Research Centre, Eötvös Loránd Research Network, Szeged, Hungary.; Institute of AI for Health, Helmholtz Zentrum München, Neuherberg, Germany.; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland., Piraud M; Helmholtz AI, Helmholtz Zentrum München, Neuherberg, Germany., Ertürk A; Institute for Tissue Engineering and Regenerative Medicine, Helmholtz Zentrum München, Neuherberg, Germany.; Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians University Munich, Munich, Germany.; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.; School of Medicine, Koç University, İstanbul, Turkey., Samakovlis C; SciLifeLab and Department of Molecular Biosciences, Stockholm University, Stockholm, Sweden.; Cardiopulmonary Institute, Justus Liebig University, Giessen, Germany., Theis FJ; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany. fabian.theis@helmholtz-munich.de.; School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany. fabian.theis@helmholtz-munich.de.; School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. fabian.theis@helmholtz-munich.de.
Source: Nature methods [Nat Methods] 2024 Dec; Vol. 21 (12), pp. 2260-2270. Date of Electronic Publication: 2024 Nov 18.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1548-7105
DOI:10.1038/s41592-024-02496-z