Author

S. Viknander

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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Biochemistry· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein folding & dynamics· 2 Research Focus:benchmarking· 1 Assay:protein sequence· 1 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1 Organism:yeast· 1

Frequent Co-Authors

A. Zelezniak· 2 shared X. Fu· 2 shared C. Goldin· 1 shared F. Buric· 1 shared J. Zrimec· 1 shared K. K. Yang· 1 shared L. Szyrwiel· 1 shared M. Muelleder· 1 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersEvolutionary Biology

A. Zelezniak

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2 papers

Recent·Most cited

The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost.

F. Buric, S. Viknander, X. Fu, O. Lemke, J. Zrimec, L. Szyrwiel, M. Muelleder, M. Ralser, A. Zelezniak

This study shows that amino acid sequences determine protein abundance by affecting conformational stability and synthesis cost, using deep learning and yeast experiments.

bioRxiv · Oct 2, 2023Evolutionary Biology

Computational Scoring and Experimental Evaluation of Enzymes Generated by Neural Networks

S. R. Johnson, X. Fu, S. Viknander, C. Goldin, S. Monaco, A. Zelezniak, K. K. Yang

The paper evaluates computational metrics for predicting enzyme activity in sequences generated by three models and finds that existing metrics like sequence identity and AlphaFold2 scores are not predictive.

bioRxiv · Mar 4, 2023Biochemistry