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Supervised Learning Method For The Prediction Of Subcellular Localization Of Proteins Using Amino Acid And Amino Acid Pair Composition, Tanwir Habib, Chaoyang Zhang, Jack Y. Yang, Mary Qu Yang, Youping Deng
Supervised Learning Method For The Prediction Of Subcellular Localization Of Proteins Using Amino Acid And Amino Acid Pair Composition, Tanwir Habib, Chaoyang Zhang, Jack Y. Yang, Mary Qu Yang, Youping Deng
Faculty Publications
Background
Occurrence of protein in the cell is an important step in understanding its function. It is highly desirable to predict a protein's subcellular locations automatically from its sequence. Most studied methods for prediction of subcellular localization of proteins are signal peptides, the location by sequence homology, and the correlation between the total amino acid compositions of proteins. Taking amino-acid composition and amino acid pair composition into consideration helps improving the prediction accuracy.
Results
We constructed a dataset of protein sequences from SWISS-PROT database and segmented them into 12 classes based on their subcellular locations. SVM modules were trained to …