Author

R. Akbar

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Immunology· 4

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:drug response / drug discovery· 2 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Assay:CITE-seq· 1

Frequent Co-Authors

A. Slabodkin· 4 shared G. K. Sandve· 4 shared I. Snapkov· 4 shared L. Scheffer· 4 shared M. Pavlovic· 4 shared P. A. Robert· 4 shared V. Greiff· 4 shared B. B. Mehta· 3 shared

Activity by Year

2020-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersImmunology

A. Slabodkin

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Author profile →

4 papers

Recent·Most cited

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

R. Akbar, P. A. Robert, C. R. Weber, M. Widrich, R. Frank, M. Pavlovic, L. Scheffer, M. Chernigovskaya, I. Snapkov, A. Slabodkin, B. B. Mehta, E. Miho, F. Lund-Johansen, J. T. Andersen, S. Hochreiter, , V. Greiff

This paper demonstrates that deep generative models can design high-affinity, developable antibodies at scale using synthetic data and transfer learning.

bioRxiv · Jul 8, 2021Immunology

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for real-world antibody specificity prediction

P. A. Robert, R. Akbar, R. Frank, M. Pavlovic, M. Widrich, I. Snapkov, A. Slabodkin, M. Chernigovskaya, L. Scheffer, E. Smorodina, P. Rawat, B. B. Mehta, M. H. Vu, I. Froberg Mathisen, A. Prosz, , V. Greiff

The paper introduces Absolut!, a software suite generating synthetic antibody-antigen structures to benchmark machine learning methods for antibody specificity prediction.

bioRxiv · Jul 6, 2021Immunology

Individualized VDJ recombination predisposes the available Ig sequence space

A. Slabodkin, M. Chernigovskaya, I. Mikocziova, R. Akbar, L. Scheffer, M. Pavlovic, H. Bashour, I. Snapkov, B. B. Mehta, C. R. Weber, J. Gutierrez-Marcos, L. M. Sollid, I. H. Haff, G. K. Sandve, P. A. Robert, V. Greiff

The paper shows that VDJ recombination rules vary between individuals, leading to individual-specific Ig sequence spaces.

bioRxiv · Apr 19, 2021Immunology

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

R. Akbar, P. A. Robert, M. Pavlovic, J. R. Jeliazkov, I. Snapkov, A. Slabodkin, C. R. Weber, L. Scheffer, E. Miho, I. H. Haff, D. T. Tryslew Haug, F. Lund-Johansen, Y. Safonova, G. K. Sandve, V. Greiff

The paper identifies a compact vocabulary of paratope-epitope interaction motifs that enables machine learning prediction of antibody-antigen binding.

bioRxiv · Mar 4, 2020Immunology