Author

K. E. Johnston

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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Bioengineering· 3

Signature Assays, Organisms & Methods

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Research Focus:protein design· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:protein sequence· 1 Assay:protein structure· 1 Assay:proteomics· 1

Frequent Co-Authors

F. H. Arnold· 2 shared A. Madani· 1 shared B. J. Wittmann· 1 shared B. Wittmann· 1 shared C. Dallago· 1 shared F.-Z. Li· 1 shared J. Ducharme· 1 shared J. Mou· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersBioengineering

F. H. Arnold

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3 papers

Recent·Most cited

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

J. Yang, J. Ducharme, K. E. Johnston, F.-Z. Li, Y. Yue, F. H. Arnold

DeCOIL optimizes degenerate codon libraries for ML-assisted protein engineering to generate diverse and high-fitness protein variants.

bioRxiv · May 11, 2023Bioengineering

evSeq: Cost-Effective Amplicon Sequencing of Every Variant in a Protein Library

B. J. Wittmann, K. E. Johnston, P. J. Almhjell, F. H. Arnold

evSeq enables cost-effective sequencing of every protein variant in a library, making extensive sequence-fitness data collection practical.

bioRxiv · Nov 18, 2021Bioengineering

FLIP: Benchmark tasks in fitness landscape inference for proteins

C. Dallago, J. Mou, K. E. Johnston, B. Wittmann, N. Bhattacharya, S. L. Goldman, A. Madani, K. K. Yang

FLIP introduces a benchmark for fitness landscape inference in proteins, focusing on function prediction and model generalization in protein engineering scenarios.

bioRxiv · Nov 9, 2021 · PreprintBioengineering