MOSTPLAS: a self-correction multi-label learning model for plasmid host range prediction.

Journal: Bioinformatics (Oxford, England)
PMID:

Abstract

MOTIVATION: Plasmids play an essential role in horizontal gene transfer, aiding their host bacteria in acquiring beneficial traits like antibiotic and metal resistance. There exist some plasmids that can transfer, replicate, or persist in multiple organisms. Identifying the relatively complete host range of these plasmids provides insights into how plasmids promote bacterial evolution. To achieve this, we can apply multi-label learning models for plasmid host range prediction. However, there are no databases providing the detailed and complete host labels of these broad-host-range plasmids. Without adequate well-annotated training samples, learning models can fail to extract discriminative feature representations for plasmid host prediction.

Authors

  • Wei Zou
    the Third Branch of Department of Acupuncture and Moxibustion, the First Affiliated Hospital of Heilongjiang University of CM, Harbin 150040.
  • Yongxin Ji
    Department of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, China.
  • Jiaojiao Guan
    School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China.
  • Yanni Sun
    Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.