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High-Throughput Machine Learning-Aided Antibody Discovery for Cell Surface Antigens

2025-05-15

Abstract excerpt

Machine learning (ML) has the potential to revolutionize antibody design and selection, but its success depends on access to extensive, well-curated datasets of antibody-antigen interactions. To address this need, we developed a synthetic Fab yeast display library optimized for seamless ML integration, focusing on sequence diversity within the CDRH3 loop. The library incorporates key sequence features derived from...

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Identifiers and source

Literature Corpus work
b095db23-2195-52b9-b3e0-5d4c1dd72685
DOI
10.1101/2025.05.15.650607
Open publication

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High-Throughput Machine Learning-Aided Antibody Discovery for Cell Surface AntigensDOI 10.1101/2025.05.15.650607
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