Group members

Tran TT, Vaage EB, Mehta A, Chopra A, Tietze L, Kolderup A, Anthi A, König M, Nygaard G, Lind A, Müller F, Nissen-Meyer LS, Magnus P, Trogstad L, Mjaaland S, Søraas A, Midtvedt K, Åsberg A, Barratt-Due A, Medhus AW, Høivik ML, Lundin K, Karlsen RF, Dahle R, Danielsson K et al. (2023)
Author Correction: Titers of antibodies against ancestral SARS-CoV-2 correlate with levels of neutralizing antibodies to multiple variants
NPJ Vaccines, 8 (1), 4
DOI 10.1038/s41541-023-00600-6, PubMed 36697432

Akbar R, Bashour H, Rawat P, Robert PA, Smorodina E, Cotet TS, Flem-Karlsen K, Frank R, Mehta BB, Vu MH, Zengin T, Gutierrez-Marcos J, Lund-Johansen F, Andersen JT, Greiff V (2022)
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
MAbs, 14 (1), 2008790
DOI 10.1080/19420862.2021.2008790, PubMed 35293269

Akbar R, Robert PA, Weber CR, Widrich M, Frank R, Pavlović M, Scheffer L, Chernigovskaya M, Snapkov I, Slabodkin A, Mehta BB, Miho E, Lund-Johansen F, Andersen JT, Hochreiter S, Hobæk Haff I, Klambauer G, Sandve GK, Greiff V (2022)
In silico proof of principle of machine learning-based antibody design at unconstrained scale
MAbs, 14 (1), 2031482
DOI 10.1080/19420862.2022.2031482, PubMed 35377271