Jump to main content
Jump to site search

Issue 4, 2014
Previous Article Next Article

Predicting essential genes in prokaryotic genomes using a linear method: ZUPLS

Author affiliations

Abstract

An effective linear method, ZUPLS, was developed to improve the accuracy and speed of prokaryotic essential gene identification. ZUPLS only uses the Z-curve and other sequence-based features. Such features can be calculated readily from the DNA/amino acid sequences. Therefore, no well-studied biological network knowledge is required for using ZUPLS. This significantly simplifies essential gene identification, especially for newly sequenced species. ZUPLS can also select necessary features automatically by embedding the uninformative variable elimination tool into the partial least squares classifier. No optimized modelling parameters are needed. ZUPLS has been used, herein, to predict essential genes of 12 remotely related prokaryotes to test its performance. The cross-organism predictions yielded AUC (Area Under the Curve) scores between 0.8042 and 0.9319 by using E. coli genes as the training samples. Similarly, ZUPLS achieved AUC scores between 0.8111 and 0.9371 by using B. subtilis genes as the training samples. We also compared it with the best available results of the existing approaches for further testing. The improvement of the AUC score in predicting B. subtilis essential genes using E. coli genes was 0.13. Additionally, in predicting E. coli essential genes using P. aeruginosa genes, the significant improvement was 0.10. Similarly, the exceptional improvement of the average accuracy of M. pulmonis using M. genitalium and M. pulmonis genes was 14.7%. The combined superior feature extraction and selection power of ZUPLS enable it to give reliable prediction of essential genes for both Gram-positive/negative organisms and rich/poor culture media.

Graphical abstract: Predicting essential genes in prokaryotic genomes using a linear method: ZUPLS

Back to tab navigation

Supplementary files

Publication details

The article was received on 12 Nov 2013, accepted on 13 Feb 2014 and first published on 14 Feb 2014


Article type: Paper
DOI: 10.1039/C3IB40241J
Citation: Integr. Biol., 2014,6, 460-469
  • Open access: Creative Commons BY-NC license
  •   Request permissions

    Predicting essential genes in prokaryotic genomes using a linear method: ZUPLS

    K. Song, T. Tong and F. Wu, Integr. Biol., 2014, 6, 460
    DOI: 10.1039/C3IB40241J

    This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material and it is not used for commercial purposes.

    Reproduced material should be attributed as follows:

    • For reproduction of material from NJC:
      [Original citation] - Published by The Royal Society of Chemistry (RSC) on behalf of the Centre National de la Recherche Scientifique (CNRS) and the RSC.
    • For reproduction of material from PCCP:
      [Original citation] - Published by the PCCP Owner Societies.
    • For reproduction of material from PPS:
      [Original citation] - Published by The Royal Society of Chemistry (RSC) on behalf of the European Society for Photobiology, the European Photochemistry Association, and RSC.
    • For reproduction of material from all other RSC journals:
      [Original citation] - Published by The Royal Society of Chemistry.

    Information about reproducing material from RSC articles with different licences is available on our Permission Requests page.

Search articles by author

Spotlight

Advertisements