Engineering

Engineering

ISSN Print: 1947-3931
ISSN Online: 1947-394X
www.scirp.org/journal/eng
E-mail: eng@scirp.org
"Semantic Similarity over Gene Ontology for Multi-Label Protein Subcellular Localization"
written by Shibiao Wan, Man-Wai Mak, Sun-Yuan Kung,
published by Engineering, Vol.5 No.10B, 2013
has been cited by the following article(s):
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[2] Use of Chou's 5-steps rule to predict the subcellular localization of gram-negative and gram-positive bacterial proteins by multi-label learning based on gene …
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[3] Gram-LocEN: Interpretable prediction of subcellular multi-localization of Gram-positive and Gram-negative bacterial proteins
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[4] Transductive Learning for Multi-Label Protein Subchloroplast Localization Prediction
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[5] Study of Protein Subcellular Localization Prediction: A Review
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[6] Ensemble linear neighborhood propagation for predicting subchloroplast localization of multi-location proteins
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[7] Mem-ADSVM: A Two-Layer Multi-Label Predictor for Identifying Multi-Functional Types of Membrane Proteins
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[8] Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins
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[9] Supplementary Materials for LNP-Chlo
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[10] Symbiosis-based alternative learning multi-swarm particle swarm optimization
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[11] Supplementary Materials for EnTrans-Chlo
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[12] mLASSO-Hum: A LASSO-based interpretable human-protein subcellular localization predictor
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[13] Mem-mEN: Predicting Multi-Functional Types of Membrane Proteins by Interpretable Elastic Nets
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[14] Predicting subcellular localization of multi-location proteins by improving support vector machines with an adaptive-decision scheme
International Journal of Machine Learning and Cybernetics, 2015
[15] Machine learning for protein subcellular localization prediction
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[16] HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location Proteins
PloS one, 2014
[17] ENSEMBLE RANDOM PROJECTION FOR MULTI-LABEL CLASSIFICATION WITH APPLICATION TO PROTEIN SUBCELLULAR LOCALIZATION
S Wan, MW Mak, B Zhang, Y Wang, SY Kung - eie.polyu.edu.hk, 2014
[18] R3P-Loc: A compact multi-label predictor using ridge regression and random projection for protein subcellular localization
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[19] HybridGO-Loc: Mining Hybrid Features on Gene Ontology for Predicting Subcellular Localization of Multi-Location
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[20] Protein subcellular localization: gene ontology based machine learning approaches
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[21] Dept. of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong, SAR, China
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on. IEEE, 2013., 2013
[22] An Ensemble Classifier with Random Projection for Predicting Multi-label Protein Subcellular Localization
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