Prediction of Protein Subcellular Multi-localization by Using a Min-Max Modular Support Vector Machine

Yang Yang; Bao‐Liang Lu

doi:10.1007/978-3-642-03156-4_14

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Prediction of Protein Subcellular Multi-localization by Using a Min-Max Modular Support Vector Machine

Yang Yang Bao‐Liang Lu

Year: 2009 Advances in intelligent and soft computing Pages: 133-143 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-642-03156-4_14

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Keywords:

Support vector machine Classifier (UML) Computer science Subcellular localization Artificial intelligence Modular design Machine learning Gene ontology Protein subcellular localization prediction Pattern recognition (psychology) Data mining Biology Gene

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Machine Learning in Bioinformatics

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

RNA and protein synthesis mechanisms

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Biochemical and Structural Characterization

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Prediction of Protein Subcellular Multi-localization by Using a Min-Max Modular Support Vector Machine

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