In silico proof of principle of machine learning-based antibody design at unconstrained scale-Reference-Cited by-同舟云学术

In silico proof of principle of machine learning-based antibody design at unconstrained scale

Published:2022-04-04 Issue:1 Volume:14 Page:
ISSN:1942-0862
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language:en
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Author:

Akbar Rahmad¹^ORCID,Robert Philippe A.¹^ORCID,Weber Cédric R.²^ORCID,Widrich Michael³^ORCID,Frank Robert¹^ORCID,Pavlović Milena⁴^ORCID,Scheffer Lonneke⁴^ORCID,Chernigovskaya Maria¹^ORCID,Snapkov Igor¹^ORCID,Slabodkin Andrei¹^ORCID,Mehta Brij Bhushan¹^ORCID,Miho Enkelejda⁵^ORCID,Lund-Johansen Fridtjof¹^ORCID,Andersen Jan Terje¹⁶^ORCID,Hochreiter Sepp³⁷^ORCID,Hobæk Haff Ingrid⁸,Klambauer Günter³^ORCID,Sandve Geir Kjetil⁴^ORCID,Greiff Victor¹^ORCID

Affiliation:

1. Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway

2. Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland

3. Ellis Unit Linz and Lit Ai Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria

4. Department of Informatics, University of Oslo, Oslo, Norway

5. Institute of Medical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland

6. Institute of Clinical Medicine, Department of Pharmacology, University of Oslo, Oslo, Norway

7. Institute of Advanced Research in Artificial Intelligence (IARAI), Austria

8. Department of Mathematics, University of Oslo, Oslo, Norway

Funder

the Leona M.and Harry B.Helmsley Charitable Trust

UiO World-Leading Research Community

LifeScience Convergence Environment Immunolingo

EU Horizon 2020 iReceptorplus

Research Council of Norway FRIPRO

Research Council of Norway IKTPLUSS

Norwegian Cancer Society

Publisher