dc.contributor.author | Magnussen, Eirik Almklov | |
dc.contributor.author | Zimmermann, Boris | |
dc.contributor.author | Blazhko, Uladzislau | |
dc.contributor.author | Dzurendová, Simona | |
dc.contributor.author | Dupuy--Galet, Benjamin Xavier | |
dc.contributor.author | Byrtusova, Dana | |
dc.contributor.author | Muthreich, Florian | |
dc.contributor.author | Tafintseva, Valeria | |
dc.contributor.author | Liland, Kristian Hovde | |
dc.contributor.author | Tøndel, Kristin | |
dc.contributor.author | Shapaval, Volha | |
dc.contributor.author | Kohler, Achim | |
dc.date.accessioned | 2023-03-27T08:49:02Z | |
dc.date.available | 2023-03-27T08:49:02Z | |
dc.date.created | 2023-01-13T13:14:47Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Communications chemistry. 2022, 5 (1), . | |
dc.identifier.issn | 2399-3669 | |
dc.identifier.uri | https://hdl.handle.net/11250/3060513 | |
dc.language.iso | eng | |
dc.title | Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra | |
dc.title.alternative | Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra | |
dc.type | Peer reviewed | |
dc.type | Journal article | |
dc.description.version | publishedVersion | |
dc.source.pagenumber | 10 | |
dc.source.volume | 5 | |
dc.source.journal | Communications chemistry | |
dc.source.issue | 1 | |
dc.identifier.doi | 10.1038/s42004-022-00792-3 | |
dc.identifier.cristin | 2106580 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |