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ZENODO
Software . 2023
License: https://opensource.org/licenses/MIT
Data sources: Datacite
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Data sources: Datacite
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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, Ruochi; Wang, Yu; Zhang, Lu; +1 Authors

doi: 10.5281/zenodo.7656350 , 10.5281/zenodo.7657016

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 multi-property constraints. Publication: TBA Files included in this release: 1.pipeline.jpg: the workflow of AB-Gen. charlesxu90/ab-gen-v1.0.zip: the source code of AB-Gen. data.zip: the filtered datasets to train the prior model, the pretrained models, and the designed sequences.

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Keywords

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

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selected citations
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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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