Computational Prediction of Protein Epsilon Lysine Acetylation Sites Based on a Feature Selection Method-Reference-Cited by-同舟云学术

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Computational Prediction of Protein Epsilon Lysine Acetylation Sites Based on a Feature Selection Method

Published:2017-10-23 Issue:7 Volume:20 Page:
ISSN:1386-2073
Container-title:Combinatorial Chemistry & High Throughput Screening
language:en
Short-container-title:CCHTS

Author:

Gao JianZhao¹,Tao Xue-Wen²,Zhao Jia³,Feng Yuan-Ming²,Cai Yu-Dong⁴,Zhang Ning²

Affiliation:

1. School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China

2. Department of Biomedical Engineering, Tianjin Key Lab of Biomedical Engineering Measurement, Tianjin University, Tianjin, China

3. Biomedical Research Center, CODBIO Company Ltd., Tianjin, China

4. School of Life Science, Shanghai University, Shanghai, China

Publisher

Bentham Science Publishers Ltd.

Subject

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

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1. predForm-Site: Formylation site prediction by incorporating multiple features and resolving data imbalance;Computational Biology and Chemistry;2021-10

2. CirBiTree: Citrullination Site Inference Based on a Fuzzy Neural Network and Flexible Neural Tree;Scientific Programming;2020-11-28

3. iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods;Computers in Biology and Medicine;2018-09

4. Prediction of citrullination sites by incorporating k-spaced amino acid pairs into Chou's general pseudo amino acid composition;Gene;2018-07

5. SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins;International Journal of Molecular Sciences;2018-06-15

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