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Antibody library design with Transformer and Deep Reinforcement Learning -- source code and data

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 20 Feb 2023 English Publisher:Zenodo
Authors: Xu, Xiaopeng; Xu, Tiantian; Zhou, Juexiao; Liao, Xingyu; Zhang, Lu; Gao, Xin;

doi: 10.5281/zenodo.7656351

Antibody library design with Transformer and Deep Reinforcement Learning -- source code and data

Abstract

This is the source code for AB-Gen, a tool for antibody library design. It can efficiently explore the antibody space and design CDRH3 sequences that fulfill muti-property constaints.

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Keywords

Transformer, Reinforcement learning, Generative modeling, Protein design, Multi-property optimization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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