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Genetic Algorithm Mutations for Molecules with a Hybrid Language Model-Based GAN Architecture

Authors: Bhowmik, Debsindhu; Zhang, Pei; Fox, Zachary; Irle, Stephan; Gounley, John;

Genetic Algorithm Mutations for Molecules with a Hybrid Language Model-Based GAN Architecture

Abstract

LM-GAN Molecules Using a language model on GAN architechture to generate molecules. Generated molecules from this LM-GAN are produced by following the process of randomly masking input molecules to this architechture and then using the LM-GAN model to make our predictions. Genetic algorithm is performed for optimizing generated population of molecules. To get more information of our langugage model using genetic algorithm please see our earlier work. Dependencies rdkit pytorch transformers Example An example script is provided here for using this LM-GAN model. Please create a results directory before running. To perform optimization without LM-GAN model, please use the following flag in command '--generator_only':

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Keywords

Genetic Algorithm, Masked Language Model, Molecule Design, Generative Adversarial Network

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citations
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).
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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.
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