Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs (English)
- New search for: Hu, Yan
- New search for: Lu, Yi
- New search for: Wang, Shuo
- New search for: Zhang, Mengying
- New search for: Qu, Xiaosheng
- New search for: Niu, Bing
- New search for: Hu, Yan
- New search for: Lu, Yi
- New search for: Wang, Shuo
- New search for: Zhang, Mengying
- New search for: Qu, Xiaosheng
- New search for: Niu, Bing
In:
Current Drug Targets
;
20
, 5
;
488-500
;
2019
-
ISSN:
- Article (Journal) / Electronic Resource
-
Title:Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs
-
Additional title:CDT
-
Contributors:Hu, Yan ( author ) / Lu, Yi ( author ) / Wang, Shuo ( author ) / Zhang, Mengying ( author ) / Qu, Xiaosheng ( author ) / Niu, Bing ( author )
-
Published in:Current Drug Targets ; 20, 5 ; 488-500
-
Publisher:
- New search for: Bentham Science Publishers Ltd.
-
Publication date:2019-04-01
-
Size:13 pages
-
ISSN:
-
Type of media:Article (Journal)
-
Type of material:Electronic Resource
-
Language:English
-
Keywords:Machine learning (ML) , anticancer drugs , linear discriminant analysis (LDA) , principal components analysis (PCA) , support vector machine (SVM) , random forest (RF) , k-nearest neighbor (kNN) , deep learning , web servers. , Drug Design and Discovery , Neuroscience , Oncology and Cancer Research , Pharmacology
-
Source:
Table of contents – Volume 20, Issue 5
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 479
-
The Computational Methods in Drug Targets DiscoveryLin, Hao et al. | 2019
- 481
-
Recent Advances in Computational Methods for Identifying Anticancer PeptidesFeng, Pengmian / Wang, Zhenyi et al. | 2019
- 488
-
Application of Machine Learning Approaches for the Design and Study of Anticancer DrugsHu, Yan / Lu, Yi / Wang, Shuo / Zhang, Mengying / Qu, Xiaosheng / Niu, Bing et al. | 2019
- 501
-
Molecular Docking: Challenges, Advances and its Use in Drug Discovery PerspectiveSaikia, Surovi / Bordoloi, Manobjyoti et al. | 2019
- 522
-
Established and In-trial GPCR Families in Clinical Trials: A Review for Target SelectionSaikia, Surovi / Bordoloi, Manobjyoti / Sarmah, Rajeev et al. | 2019
- 540
-
A Survey for Predicting Enzyme Family Classes Using Machine Learning MethodsTan, Jiu-Xin / Lv, Hao / Wang, Fang / Dao, Fu-Ying / Chen, Wei / Ding, Hui et al. | 2019
- 551
-
Understanding Membrane Protein Drug Targets in Computational PerspectiveGong, Jianting / Chen, Yongbing / Pu, Feng / Sun, Pingping / He, Fei / Zhang, Li / Li, Yanwen / Ma, Zhiqiang / Wang, Han et al. | 2019
- 565
-
Towards Computational Models of Identifying Protein Ubiquitination SitesWang, Lidong / Zhang, Ruijun et al. | 2019
- 579
-
Prediction of Ion Channels and their Types from Protein Sequences: Comprehensive Review and Comparative AssessmentGao, Jianzhao / Miao, Zhen / Zhang, Zhaopeng / Wei, Hong / Kurgan, Lukasz et al. | 2019
- 593
-
In Silico Design and Synthesis of Targeted Curcumin Derivatives as Xanthine Oxidase InhibitorsMalik, Neelam / Dhiman, Priyanka / Khatkar, Anurag et al. | 2019