Journal
BMC BIOINFORMATICS
Volume 20, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s12859-019-3232-4
Keywords
Physicochemical properties; Position-specific score matrix; Gene ontology; Principal component analysis; Support vector machine
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Funding
- National Natural Science Foundation of China [61762035]
- Hainan Provincial Natural Science Foundation of China [119MS037]
- Zhejiang Provincial Natural Science Foundation of China [LY18F020027]
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Background: Subcellular localization prediction of protein is an important component of bioinformatics, which has great importance for drug design and other applications. A multitude of computational tools for proteins subcellular location have been developed in the recent decades, however, existing methods differ in the protein sequence representation techniques and classification algorithms adopted. Results: In this paper, we firstly introduce two kinds of protein sequences encoding schemes: dipeptide information with space and Gapped k-mer information. Then, the Gapped k-mer calculation method which is based on quad-tree is also introduced. Conclusions: >From the prediction results, this method not only reduces the dimension, but also improves the prediction precision of protein subcellular localization.
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