This directory includes the published data science related projects.
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Hao M, Li Y, Wang Y, Zhang S. Prediction of PKCθ inhibitory activity using the random forest algorithm. International Journal of Molecular Sciences 11, 3413-3433 (2010).
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Hao M, Li Y, Wang Y, Zhang S. Prediction of P2Y12 antagonists using a novel genetic algorithm-support vector machine coupled approach. Analytica Chimica Acta 690, 53-63 (2011).
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Hao M, Li Y, Wang Y, Zhang S. A classification study of respiratory syncytial virus (RSV) inhibitors by variable selection with random forest. International Journal of Molecular Sciences 12, 1259-1280 (2011).
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Hao M, Li Y, Wang Y, Zhang S. A classification study of human β3-adrenergic receptor agonists using BCUT descriptors. Molecular Diversity 15, 877-887 (2011).
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Hao M, Zhang S, Qiu J. Toward the prediction of FBPase inhibitory activity using chemoinformatics methods. International Journal of Molecular Sciences 13, 7015-7037 (2012).
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Hao M, Wang Y, Bryant S. An efficient algorithm coupled with synthetic minority oversampling technique to classify imbalanced PubChem BioAssay data. Analytica Chimica Acta 806, 117-127 (2014).
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Hao M, Wang Y, Bryant S. Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique. Analytica Chimica Acta 909, 41-50 (2016).
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Hao M, Bryant S, Wang Y. Predicting drug-target interactions by dual-network integrated logistic matrix factorization. Scientific Reports 7, 40376 (2017).
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Hao M, Bryant S, Wang Y. Open-source chemogenomic data-driven algorithms for predicting drug-target interactions. Briefings in Bioinformatics (2018).
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Hao M, Bryant S, Wang Y. A new chemoinformatics approach with improved strategies for effective predictions of potential drugs. Journal of Cheminformatics 10, 50 (2018).