Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine-Reference-Cited by-同舟云学术

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Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine

Published:2017-05 Issue: Volume:78 Page:41-46
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Xiang Qilin,Liao Bo,Li Xianhong,Xu Huimin,Chen Jing,Shi Zhuoxing,Dai Qi,Yao Yuhua

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference48 articles.

1. Recent progress in protein subcellular location prediction;Chou;Anal Biochem,2007

2. Support vector machine-based method for subcellular location of human proteins using amino acid compositions, their order and similarity search;Garg;J Biol Chem,2005

3. HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins;Wan;PLoS One,2014

4. Prediction of protein subcellular locations with feature selection and analysis;Cai;Protein Pept Lett,2010

5. iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites;Wu;Mol Biosyst,2011

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