ArticleFrontiers in microbiology2026
Chlamy_ChloroPred: a deep learning-based, highly accurate binary classifier for chloroplast protein prediction in the model microalga,
Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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11 authors.
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Abstract
Introduction: The chloroplast, a living relic of an ancient endosymbiotic interaction between a microalga and a microbe and the principal subcellular organelle responsible for biological CO Methods: To address the limitation, we herein present Chlamy_ChloroPred, a newly developed deep learning-based framework composed of multi-layered artificial neural networks, carefully designed to perform binary classification of chloroplast proteins in the model photosynthetic microorganism, Results and discussion: Our model achieved an accuracy of 0.8462 for the Conclusion: We developed a deep learning-based framework, Chlamy_ChloroPred, that integrates carefully designed neural layers with low computational complexity, achieving high predictive accuracy and interpretability. We believe that Chlamy_ChloroPred represents a compelling alternative to existing predictors, especially when accurate inference of chloroplast proteins is required.
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