Protein–protein interaction sites prediction by ensembling SVM and sample-weighted random forests

Predicting protein–protein interaction (PPI) sites from protein sequences is still a challenge task in computational biology. There exists a severe class imbalance phenomenon in predicting PPI sites, which leads to a decrease in overall performance for traditional statistical machine-learning-based...

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Veröffentlicht in:	Neurocomputing (Amsterdam) 2016-06, Vol.193, p.201-212
Hauptverfasser:	Wei, Zhi-Sen, Han, Ke, Yang, Jing-Yu, Shen, Hong-Bin, Yu, Dong-Jun
Format:	Artikel
Sprache:	eng
Schlagworte:	Classifier ensemble Classifiers Computation Imbalanced learning Protein–protein interaction sites Random forests Representations Samples Sequence-based prediction Statistical analysis Statistical methods Support vector machine Support vector machines Training
Online-Zugang:	Volltext
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