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Machine Learning Deciphers Genotype and Ammonium as Key Factors for the Micropropagation of Bryophyllum sp. Medicinal Plants.
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- Horticulturae, 2022, v. 8, n. 11, p. 987, doi. 10.3390/horticulturae8110987
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- Article
Neurofuzzy logic predicts a fine-tuning metabolic reprogramming on elicited Bryophyllum PCSCs guided by salicylic acid.
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- Frontiers in Plant Science, 2022, v. 13, p. 1, doi. 10.3389/fpls.2022.991557
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- Article
The Combination of Untargeted Metabolomics and Machine Learning Predicts the Biosynthesis of Phenolic Compounds in Bryophyllum Medicinal Plants (Genus Kalanchoe).
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- Plants (2223-7747), 2021, v. 10, n. 11, p. 2430, doi. 10.3390/plants10112430
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- Article
Machine Learning Unmasked Nutritional Imbalances on the Medicinal Plant Bryophyllum sp. Cultured in vitro.
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- Frontiers in Plant Science, 2020, v. 11, p. N.PAG, doi. 10.3389/fpls.2020.576177
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- Article
From Ethnomedicine to Plant Biotechnology and Machine Learning: The Valorization of the Medicinal Plant Bryophyllum sp.
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- Pharmaceuticals (14248247), 2020, v. 13, n. 12, p. 444, doi. 10.3390/ph13120444
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- Article
Machine Learning Technology Reveals the Concealed Interactions of Phytohormones on Medicinal Plant In Vitro Organogenesis.
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- Biomolecules (2218-273X), 2020, v. 10, n. 5, p. 746, doi. 10.3390/biom10050746
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- Article
Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.
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- Antioxidants, 2020, v. 9, n. 3, p. 210, doi. 10.3390/antiox9030210
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- Article