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Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

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Editorial

The Application of Machine Learning Techniques in Protein Drugs and Drug Targets Recognition

Author(s): Hui Ding

Volume 20, Issue 3, 2019

Page: [168 - 169] Pages: 2

DOI: 10.2174/138920022003190424105144

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[1]
Dao, F.Y.; Lv, H.; Wang, F.; Feng, C.Q.; Ding, H.; Chen, W.; Lin, H. Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique. Bioinformatics, 2018. [Epub ahead of print].
[2]
Feng, C.Q.; Zhang, Z.Y.; Zhu, X.J.; Lin, Y.; Chen, W.; Tang, H.; Lin, H. iTerm-PseKNC: A sequence-based tool for predicting bacterial transcriptional terminators. Bioinformatics, 2018. [Epub ahead of print].
[3]
Stephenson, N.; Shane, E.; Chase, J.; Rowland, J.; Ries, D.; Justice, N.; Zhang, J.; Chan, L.; Cao, R. Survey of machine learning techniques in drug discovery. Curr. Drug Metab., 2018. [Epub ahead of print].
[4]
Ning, L.; He, B.; Zhou, P.; Derda, R.; Huang, J. Molecular Design of Peptide-Fc Fusion Drugs. Curr. Drug Metab., 2018. [Epub ahead of print].
[5]
Chen, W.; Feng, P.; Liu, T.; Jin, D. Recent advances in machine learning methods for predicting heat shock proteins. Curr. Drug Metab., 2018. [Epub ahead of print].
[6]
Li, Z.; Miao, Q.; Yan, F.; Meng, Y.; Zhou, P. Machine learning in quantitative protein-peptide affinity prediction: Implications for therapeutic peptide design. Curr. Drug Metab., 2018. [Epub ahead of print].
[7]
Hu, Y.; Zhao, T.; Zhang, N.; Zhang, Y.; Cheng, L. A review of recent advances and research on drug target identification methods. Curr. Drug Metab., 2018. [Epub ahead of print].
[8]
Zhang, W.; Lin, W.; Zhang, D.; Wang, S.; Shi, J.; Niu, Y. Recent advances in the machine learning-based drug-target interaction prediction. Curr. Drug Metab., 2018. [Epub ahead of print].
[9]
Zheng, N.; Wang, K.; Zhan, W.; Zhan, W.; Deng, L. Targeting virus-host protein interactions: Feature extraction and machine learning approaches. Curr. Drug Metab., 2018. [Epub ahead of print].
[10]
Yao, Y.; Xu, H.; Li, M.; Qi, Z.; Liao, B. Recent advances on prediction of human papillomaviruses risk types. Curr. Drug Metab., 2019. [Epub ahead of print].
[11]
Wei, H.H.; Yang, W.; Tang, H.; Lin, H. The development of machine learning methods in cell-penetrating peptides identification: A brief review. Curr. Drug Metab., 2018. [Epub ahead of print].
[12]
Xiong, Y.; Qiao, Y.; Kihara, D.; Zhang, H.Y.; Zhu, X.; Wei, D.Q. Survey of machine learning techniques for prediction of the isoform specificity of cytochrome p450 substrates. Curr. Drug Metab., 2018. [Epub ahead of print].
[13]
Lai, H.Y.; Chen, X.X.; Chen, W.; Tang, H.; Lin, H. Sequence-based predictive modeling to identify cancerlectins. Oncotarget,, 2017, 8, 28169-28175.

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