Learning single-cell perturbation responses using neural optimal transport.
Saved in:
| Title: | Learning single-cell perturbation responses using neural optimal transport. |
|---|---|
| Authors: | Bunne C; Department of Computer Science, ETH Zurich, Zürich, Switzerland.; AI Center, ETH Zurich, Zürich, Switzerland., Stark SG; Department of Computer Science, ETH Zurich, Zürich, Switzerland.; AI Center, ETH Zurich, Zürich, Switzerland.; Medical Informatics Unit, University of Zurich Hospital, Zürich, Switzerland.; Swiss Institute of Bioinformatics, Zurich, Switzerland., Gut G; Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland., Del Castillo JS; Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland., Levesque M; Department of Dermatology, University of Zurich Hospital, University of Zurich, Zürich, Switzerland., Lehmann KV; Department of Computer Science, ETH Zurich, Zürich, Switzerland. kjlehmann@ukaachen.de.; Cancer Research Center Cologne-Essen, Site: Center Integrated Oncology Aachen, Aachen, Germany. kjlehmann@ukaachen.de., Pelkmans L; Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland. lucas.pelkmans@mls.uzh.ch., Krause A; Department of Computer Science, ETH Zurich, Zürich, Switzerland. krausea@ethz.ch.; AI Center, ETH Zurich, Zürich, Switzerland. krausea@ethz.ch., Rätsch G; Department of Computer Science, ETH Zurich, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch.; AI Center, ETH Zurich, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch.; Medical Informatics Unit, University of Zurich Hospital, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch.; Swiss Institute of Bioinformatics, Zurich, Switzerland. gunnar.raetsch@inf.ethz.ch.; Department of Biology, ETH Zurich, Zürich, Switzerland. gunnar.raetsch@inf.ethz.ch. |
| Source: | Nature methods [Nat Methods] 2023 Nov; Vol. 20 (11), pp. 1759-1768. Date of Electronic Publication: 2023 Sep 28. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| 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 |
Be the first to leave a comment!
