PlasGUN: gene prediction in plasmid metagenomic short reads using deep learning.

Journal: Bioinformatics (Oxford, England)
Published Date: May 1, 2020

Abstract

SUMMARY: We present the first tool of gene prediction, PlasGUN, for plasmid metagenomic short-read data. The tool, developed based on deep learning algorithm of multiple input Convolutional Neural Network, demonstrates much better performance when tested on a benchmark dataset of artificial short reads and presents more reliable results for real plasmid metagenomic data than traditional gene prediction tools designed primarily for chromosome-derived short reads.

Authors

  • Zhencheng Fang
    State Key Laboratory for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Peking University, No.5 Yiheyuan Road Haidian District, Beijing 100871, China.
  • Jie Tan
    Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
  • Shufang Wu
    State Key Laboratory for Turbulence and Complex Systems and Department of Biomedical Engineering, College of Engineering, Peking University, No.5 Yiheyuan Road Haidian District, Beijing 100871, China.
  • Mo Li
    School of Computer Science and Engineering, Key Laboratory of Big Data Management and Analytics (Liaoning), Northeastern University, China.
  • Chunhui Wang
    State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Quantitative Biology, Peking University, Beijing 100871, China.
  • Yongchu Liu
    State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering and Center for Quantitative Biology, Peking University, Beijing 100871, China.
  • Huaiqiu Zhu
    Department of Biomedical Engineering, College of Engineering, and Centre for Quantitative Biology, Peking University, Beijing, China.

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