Incorporating Distance-Based Top-n-gram and Random Forest To Identify Electron Transport Proteins-Reference-Cited by-同舟云学术

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Incorporating Distance-Based Top-n-gram and Random Forest To Identify Electron Transport Proteins

Published:2019-05-28 Issue:7 Volume:18 Page:2931-2939
ISSN:1535-3893
Container-title:Journal of Proteome Research
language:en
Short-container-title:J. Proteome Res.

Author:

Ru Xiaoqing¹²^ORCID,Li Lihong²,Zou Quan¹³^ORCID

Affiliation:

1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China

2. School of Information and Electrical Engineering, Hebei University of Engineering, Handan, China

3. Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Chemistry,Biochemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jproteome.9b00250

Reference69 articles.

1. Prediction of transporter targets using efficient RBF networks with PSSM profiles and biochemical properties

2. TCDB: the Transporter Classification Database for membrane transport protein analyses and information

3. TransportDB: a relational database of cellular membrane transport systems

4. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs

5. Inferring drug-disease associations based on known protein complexes

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