ProLoc: Prediction of protein subnuclear localization using SVM with automatic selection from physicochemical composition features

Accurate prediction methods of protein subnuclear localizations rely on the cooperation between informative features and classifier design. Support vector machine (SVM) based learning methods are shown effective for predictions of protein subcellular and subnuclear localizations. This study proposes...

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Veröffentlicht in:BioSystems 2007-09, Vol.90 (2), p.573-581
Hauptverfasser: Huang, Wen-Lin, Tung, Chun-Wei, Huang, Hui-Ling, Hwang, Shiow-Fen, Ho, Shinn-Ying
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Sprache:eng
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