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Image-based & machine learning-guided multiplexed serology test for SARS-CoV-2

Single-cell extracted imaging features created in project "Image-based & machine learning-guided multiplexed serology test for SARS-CoV-2". The dataset includes train (with annotations) and test features used in the manuscript. Four SARS-CoV-2 antigens (S, N, R, M) were imaged separately with serum samples presenting IgG, IgA and IgM antibodies.

By Pietiäinen, Vilja, Polso, Minttu, Migh, Ede, Guckelsberger, Christian, Harmati, Maria, Diosdi, Akos, Turunen, Laura, Hassinen, Antti, Potdar, Swapnil, Koponen, Annika, Sebestyen, Edina Guykity, Kovacs, Ferenc, Kriston, Andras, Hollandi, Reka, Burian, Katalin, Terhes, Gabriella, Visnyovszki, Adam, Fodor, Eszter, Lacza, Zsombor, Kantele, Anu, Kolehmainen, Pekka, Kakkola, Laura, Strandin, Tomas, Levanov, Lev, Kallioniemi, Olli, Kemeny, Lajos, Julkunen, Ilkka, Vapalahti, Olli, Buzas, Krisztina, PaavDatasetReference information

Resource information

Data purpose
Research dataset
Subject
Image-based, Machine learning, SARS-CoV-2
Format
zip
Original repository
6352550
DOI
10.5281/zenodo.6352550
Credit basis
Creators in Zenodo record metadata
Access
Open files available from the original Zenodo deposit
Last checked
Nov 5, 2026
License
cc-by-4.0
Last record update
Nov 5, 2026

About this resource

Single-cell extracted imaging features created in project "Image-based & machine learning-guided multiplexed serology test for SARS-CoV-2". The dataset includes train (with annotations) and test features used in the manuscript. Four SARS-CoV-2 antigens (S, N, R, M) were imaged separately with serum samples presenting IgG, IgA and IgM antibodies.