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Discrimination of outer membrane proteins using a K-nearest neighbor method

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Summary.

Identification of outer membrane proteins (OMPs) from genome is an important task. This paper presents a k-nearest neighbor (K-NN) method for discriminating outer membrane proteins (OMPs). The method makes predictions based on a weighted Euclidean distance that is computed from residue composition. The method achieves 89.1% accuracy with 0.668 MCC (Matthews correlation coefficient) in discriminating OMPs and non-OMPs. The performance of the method is improved by including homologous information into the calculation of residue composition. The final method achieves an accuracy of 96.1%, with 0.873 MCC, 87.5% sensitivity, and 98.2% specificity. Comparisons with multiple recently published methods show that the method proposed in this study outperforms the others.

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Authors and Affiliations

  1. Department of Computer Science, Utah State University, Logan, UT, USA

    C. Yan, J. Hu & Y. Wang

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  1. C. Yan
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  2. J. Hu
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  3. Y. Wang
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Authors’ address: Changhui Yan, Old Main Hill 4205, Logan, UT 84322-4205, USA

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Yan, C., Hu, J. & Wang, Y. Discrimination of outer membrane proteins using a K-nearest neighbor method. Amino Acids 35, 65–73 (2008). https://doi.org/10.1007/s00726-007-0628-7

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  • DOI: https://doi.org/10.1007/s00726-007-0628-7

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