Author

Andrea K. Steiger

ORCID 0000-0003-1655-7973Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Synthetic Biology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1 Organism:human· 1 Assay:protein sequence· 1 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Abigail B. VenturaiD· 2 shared Christa Kohnert· 2 shared Hayley Carter· 2 shared Jahir M. GutierreziD· 2 shared John M. SuttoniD· 2 shared Joshua Bennett· 2 shared Joshua MeieriD· 2 shared Kerianne A. JacksoniD· 2 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersSynthetic Biology

Abigail B. VenturaORCID

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2 papers

Recent·Most cited

Synthetic BiologybioRxivPreprintFeb 11, 2023

Deep learning-based codon optimization with large-scale synonymous variant datasets enables generalized tunable protein expression

David A. Constant, Jahir M. Gutierrez, Anand V. Sastry…·Miles W. Gander

The paper develops deep learning models trained on synonymous variant datasets to predict and optimize protein expression in E. coli.

20 citations

E. coliprotein sequence

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Synthetic BiologybioRxivPreprintJan 8, 2023

Unlocking de novo antibody design with generative artificial intelligence

Amir Shanehsazzadeh, Matt McPartlon, George W. Kasun…·Sharrol T. Bachas

Deep generative models combined with high-throughput screening design de novo anti-HER2 antibodies without further optimization, yielding nanomolar binders functionally comparable or superior to trastuzumab.

82 citations

humanproteomics

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