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Myunghum Park

As seen in: Nature, MDPI
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Articles

Integrating molecular descriptors and fingerprints via meta-learning for aqueous solubility prediction

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By Waqar Ahmad, Rida Arshad, Myunghum Park, Hilal Tayara, Ki-Duk Song, Muhannad Dehni
| Nature Verified
Abstract Solubility strongly affects a compound’s bioavailability, formulation, and pharmacokinetics, so predicting aqueous solubility is a key challenge in drug discovery and chemical design. We present a machine learning system that uses a stacking-based meta-model and several molecular representations to predict molecular aqueous solubility.
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Antibiotics | Free Full-Text | Sedeveria pink ruby Extract-Mediated Synthesis of Gold and Silver Nanoparticles and Their Bioactivity against Livestock Pathogens and in Different Cell Lines

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By Sujung Kim, Sung-Jo Kim, Palaniselvam Kuppusamy, Myunghum Park
| MDPI
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