Author

S. Ewert

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· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:deep learning· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:optimal transport· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

D. K. Gifford· 2 shared G. Horny· 2 shared B. Carter· 1 shared C. Banholzer· 1 shared G. Liu· 1 shared H. Zeng· 1 shared J. Mueller· 1 shared J. Schilz· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioengineering

D. K. Gifford

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2 papers

Recent·Most cited

Ultra high diversity factorizable libraries for efficient therapeutic discovery

Z. Dai, S. D. Saksena, G. Horny, C. Banholzer, S. Ewert, D. K. Gifford

The paper designs factorizable libraries for therapeutic discovery using an optimization method called SAPS to generate diverse and efficient antibody CDR-H3 sequences.

bioRxiv · Jan 17, 2022 · PreprintBioengineering

Antibody Complementarity Determining Region Design Using High-Capacity Machine Learning

G. Liu, H. Zeng, J. Mueller, B. Carter, Z. Wang, J. Schilz, G. Horny, M. E. Birnbaum, S. Ewert, D. K. Gifford

This paper introduces a machine learning method to design human IgG antibodies with superior target affinity and specificity, using high-throughput data without requiring target structural information.

bioRxiv · Sep 3, 2019Immunology