Predicting subcellular localization of proteins for Gram‐negative bacteria by support vector machines based on n ‐peptide compositions
National Yang Ming Chiao Tung University · National Taiwan University · +1 more institution
Abstract
Gram-negative bacteria have five major subcellular localization sites: the cytoplasm, the periplasm, the inner membrane, the outer membrane, and the extracellular space. The subcellular location of a protein can provide valuable information about its function. With the rapid increase of sequenced genomic data, the need for an automated and accurate tool to predict subcellular localization becomes increasingly important. We present an approach to predict subcellular localization for Gram-negative bacteria. This method uses the support vector machines trained by multiple feature vectors based on n-peptide compositions. For a standard data set comprising 1443 proteins, the overall prediction accuracy reaches 89%,…
Citation impact
- FWCI
- 6.75
- Percentile
- 100%
- References
- 29
Authors
3Topics & keywords
- Periplasmic space
- Subcellular localization
- Computational biology
- Bacterial outer membrane
- Protein subcellular localization prediction
- Support vector machine
- Gram-negative bacteria
- Function (biology)