<ul><li>Researchers have developed a deep learning-based gene deletion prediction framework for growth-coupled production in genome-scale metabolic models.</li><li>The framework leverages deep learning algorithms to learn and integrate sequential gene and metabolite data representation.</li><li>It demonstrates substantial improvements over the baseline method, with an increase in overall accuracy across different metabolic models</li><li>The source code and examples for the framework are publicly available on GitHub.</li></ul>

DeepGDel: Deep Learning-based Gene Deletion Prediction Framework for Growth-Coupled Production in Genome-Scale Metabolic Models

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