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Combining Machine Learning and Homology-Based Approaches to Accurately Predict Subcellular Localization in Arabidopsis
2010
Plant Physiology
A complete map of the Arabidopsis (Arabidopsis thaliana) proteome is clearly a major goal for the plant research community in terms of determining the function and regulation of each encoded protein. Developing genome-wide prediction tools such as for localizing gene products at the subcellular level will substantially advance Arabidopsis gene annotation. To this end, we performed a comprehensive study in Arabidopsis and created an integrative support vector machine-based localization predictor
doi:10.1104/pp.110.156851
pmid:20647376
pmcid:PMC2938157
fatcat:p45dt3fkxzflto2bktbukhnhha