Machine Learning for Protein Subcellular Localization Prediction-P2P
Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature extraction, and dimensionality reduction.

Machine Learning for Protein Subcellular Localization Prediction-P2P
English | 2015 | ISBN-13: 978-1501510489 | 210 Pages | PDF, EPUB | 13.58 MB
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