[1]
Zi-Mei,, Z.; Zheng-Xing,, G; Fang, W.; Dan, Z.; Hui, D. Applications of machine learning methods in predicting nuclear receptors and their families. Med. Chem., 2020, 16, 594-604.
[2]
Shi-Hao,, L.; Zheng-Xing, G.; Dan, Z.; Zi-Mei, Z.; Jian, H.; Wuritu, Y.; Hao, L. Recent advance in predicting subcellular localization of mycobacterial protein with machine learning methods. Med. Chem., 2020, 16, 605-619.
[3]
Wei, C.; Pengmian, F.; Fulei, N. iATP: a sequence based method for identifying anti-tubercular peptides. Med. Chem., 2020, 16, 620-625.
[4]
Weiju, S.; Ying, H.; Shuo, Y.; He, Z.; Jingwen, Z.; Liang, C.; Lu, Fu The assessment of interleukin-18 on the risk of coronary heart disease. Med. Chem., 2020, 16, 626-634.
[5]
Yuchi, Z.; Xinyu, W.; Cong, Z.; Kai, L.; Yi, Z.; Jing, Z.; Pengling, G. Integrative analysis of whole-genome expression profiling and regulatory network identifies novel biomarkers for insulin resistance in leptin receptor-deficient mice. Med. Chem., 2020, 16, 635-642.
[6]
Neelam, M.; Anurag, K.; Priyanka, D. Computational analysis and synthesis of syringic acid derivatives as xanthine oxidase inhibitors. Med. Chem., 2020, 16, 643-653.