Author

Adrian W. Lange

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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Synthetic Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

Aditya A. Agarwal· 2 shared David A. YoungeriD· 2 shared David Noble· 2 shared Emily Engelhart· 2 shared James Harrang· 2 shared Kerry L. McGowaniD· 2 shared Miranda C. LahmaniD· 2 shared Randolph M. Lopez· 2 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersSynthetic Biology

Aditya A. Agarwal

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2 papers

Recent·Most cited

The Synthetic Epitope Atlas: High-Throughput Design and Validation of De Novo Antibody-Antigen Complexes

Nicholas Altieri, Joseph L. Harman, David Noble, Natasha Seelam Murakowska, Alexander Eng, Kerry L. McGowan, Davis Goodnight, Lucian DiPeso, Colleen Shikany, Emily Engelhart, Leah J. Homad, Miranda C. Lahman, Shyam Gandhi, Mackenzie Goodwin, Kendrick Herbst, , Adrian W. Lange

The paper generates and validates synthetic epitope proteins to improve de novo antibody design by combining computational design with high-throughput experimental binding data.

bioRxiv · Apr 19, 2026 · PreprintSynthetic Biology

AlphaBind, a Domain-Specific Model to Predict and Optimize Antibody-Antigen Binding Affinity

Aditya A. Agarwal, James Harrang, David Noble, Kerry L. McGowan, Adrian W. Lange, Emily Engelhart, Miranda C. Lahman, Jeffrey Adamo, Xin Yu, Oliver Serang, Kyle J. Minch, Kimberly Wellman, David A. Younger, Randolph M. Lopez, Ryan Emerson

AlphaBind predicts and optimizes antibody-antigen binding affinity using a domain-specific model trained on quantitative binding data.

mAbs · Jul 22, 2025Peer-reviewedSynthetic Biology