Tri-Cluster-Tri-Scheme-Training: Exploiting Unlabeled Data for Transmembrane Segments Prediction

Abstract

Recent work using supervised learning for protein structure prediction has achieved state-of-the-art classification performance. However, such methods are based only on labeled data, while in practice the labeled data is so few and expensive to obtain and unlabeled data is far more plentiful. An effective way to enhance the performance of the learned… (More)
DOI: 10.1109/BIBE.2009.15

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Cite this paper

@article{He2009TriClusterTriSchemeTrainingEU, title={Tri-Cluster-Tri-Scheme-Training: Exploiting Unlabeled Data for Transmembrane Segments Prediction}, author={Jieyue He and Robert W. Harrison and Phang C. Tai and Yi Pan}, journal={2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering}, year={2009}, pages={168-175} }