APA (7th ed.) Citation

Yuan, J., Yu, S., Gao, S., Gan, Y., Zhang, Y., Zhang, T., . . . Yao, W. (2016). Predicting the biological activities of triazole derivatives as SGLT2 inhibitors using multilayer perceptron neural network, support vector machine, and projection pursuit regression models. Chemometrics & Intelligent Laboratory Systems, 156, 166. https://doi.org/10.1016/j.chemolab.2016.06.002

Chicago Style (17th ed.) Citation

Yuan, Jintao, et al. "Predicting the Biological Activities of Triazole Derivatives as SGLT2 Inhibitors Using Multilayer Perceptron Neural Network, Support Vector Machine, and Projection Pursuit Regression Models." Chemometrics & Intelligent Laboratory Systems 156 (2016): 166. https://doi.org/10.1016/j.chemolab.2016.06.002.

MLA (9th ed.) Citation

Yuan, Jintao, et al. "Predicting the Biological Activities of Triazole Derivatives as SGLT2 Inhibitors Using Multilayer Perceptron Neural Network, Support Vector Machine, and Projection Pursuit Regression Models." Chemometrics & Intelligent Laboratory Systems, vol. 156, 2016, p. 166, https://doi.org/10.1016/j.chemolab.2016.06.002.