Review of Protein Subcellular Localization Prediction
Protein subcellular localization is closely related to protein functions. Protein can work only in specific subcellular positions, so protein localization in a cell is very important in studies on cytobiology, proteomics, and drug design. Protein subcellular localization prediction based on machine learning is timely and has generated great interest in the field of bioinformatics. This paper reviews the research status of this problem in recent years from the following four aspects: protein dataset construction, features extraction of protein sequence, machine learning algorithms, and web server construction. Finally, we analyzed the challenges in predicting protein subcellular localization and identified possible future research trends.
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Document Type: Research Article
Publication date: July 1, 2014
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- Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a wide range of the integration of biology with computer and information science.
The journal focuses on reviews on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.
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