Deep Visual Proteomics defines single-cell identity and heterogeneity
Deep Visual Proteomics defines single-cell identity and heterogeneity
About this item
Full title
Author / Creator
Mund, Andreas , Coscia, Fabian , Kriston, András , Hollandi, Réka , Kovács, Ferenc , Brunner, Andreas-David , Migh, Ede , Schweizer, Lisa , Santos, Alberto , Bzorek, Michael , Naimy, Soraya , Rahbek-Gjerdrum, Lise Mette , Dyring-Andersen, Beatrice , Bulkescher, Jutta , Lukas, Claudia , Eckert, Mark Adam , Lengyel, Ernst , Gnann, Christian , Lundberg, Emma , Horvath, Peter and Mann, Matthias
Publisher
New York: Nature Publishing Group US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Nature Publishing Group US
Subjects
More information
Scope and Contents
Contents
Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated...
Alternative Titles
Full title
Deep Visual Proteomics defines single-cell identity and heterogeneity
Authors, Artists and Contributors
Author / Creator
Coscia, Fabian
Kriston, András
Hollandi, Réka
Kovács, Ferenc
Brunner, Andreas-David
Migh, Ede
Schweizer, Lisa
Santos, Alberto
Bzorek, Michael
Naimy, Soraya
Rahbek-Gjerdrum, Lise Mette
Dyring-Andersen, Beatrice
Bulkescher, Jutta
Lukas, Claudia
Eckert, Mark Adam
Lengyel, Ernst
Gnann, Christian
Lundberg, Emma
Horvath, Peter
Mann, Matthias
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_swepub_primary_oai_DiVA_org_kth_324156
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_swepub_primary_oai_DiVA_org_kth_324156
Other Identifiers
ISSN
1087-0156,1546-1696
E-ISSN
1546-1696
DOI
10.1038/s41587-022-01302-5
