Computational Method for Distinguishing Lysine Acetylation, Sumoylation, and Ubiquitination using the Random Forest Algorithm with a Feature Selection Procedure-Reference-Cited by-同舟云学术

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Computational Method for Distinguishing Lysine Acetylation, Sumoylation, and Ubiquitination using the Random Forest Algorithm with a Feature Selection Procedure

Published:2018-02-13 Issue:10 Volume:20 Page:886-895
ISSN:1386-2073
Container-title:Combinatorial Chemistry & High Throughput Screening
language:en
Short-container-title:CCHTS

Author:

Wang ShaoPeng¹,Li JiaRui¹,Yuan Fei²,Chen Lei³,Huang Tao⁴,Cai Yu-Dong¹

Affiliation:

1. College of Life Science, Shanghai University, Shanghai 200444, China

2. Department of Science & Technology, Binzhou Medical University Hospital, Binzhou 256603, Shandong, China

3. College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China

4. Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. iSUMO-RsFPN: A predictor for identifying lysine SUMOylation sites based on multi-features and feature pyramid networks;Analytical Biochemistry;2024-04

2. Negative regulation of aryl hydrocarbon receptor by its lysine mutations and exposure to nickel;Molecular & Cellular Toxicology;2019-09-30

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