Fang, Jiansong

Target identification among known drugs by deep learning from heterogeneous networks

Zeng, X., Zhu, S., Lu, W., Liu, Z., Huang, J., Zhou, Y., Fang, J., Huang, Y., Guo, H., Li, L., et al. (2020) · Chemical Science

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 357

A genome-wide positioning systems network algorithm for in silico drug repurposing

Cheng, F., Lu, W., Liu, C., Fang, J., Hou, Y., Handy, D. E., Wang, R., Zhao, Y., Yang, Y., Huang, J., et al. (2019) · Nature Communications

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 215

Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer’s disease

Fang, J., Zhang, P., Zhou, Y., Chiang, C.-W., Tan, J., Hou, Y., Stauffer, S., Li, L., Pieper, A. A., Cummings, J., et al. (2021) · Nature Aging

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 206

Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease

Fang, J., Zhang, P., Wang, Q., Chiang, C.-W., Zhou, Y., Hou, Y., Xu, J., Chen, R., Zhang, B., Lewis, S. J., et al. (2022) · Alzheimer's Research & Therapy

Alzheimer's disease research and treatmentsComputational Drug Discovery Methods

Cited by 140

Discovery of neuroprotective compounds by machine learning approaches

Fang, J., Pang, X., Yan, R., Lian, W., Li, C., Wang, Q., Liu, A.-L., & Du, G.-H. (2016) · RSC Advances

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 31