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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936157 | PMC |
| http://dx.doi.org/10.1186/s12859-019-3232-4 | DOI Listing |
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