Identification of Heavy Smokers through Their Intestinal Microbiota by Data Mining Analysis

• KOBAYASHI Toshio

  Miyagi University, Japan Riken, Japan

• FUJIWARA Kenji

  Riken, Japan Yokohama Rosai Hospital, Japan

Abstract

The intestinal microbiota compositions of 92 Japanese men were identified following consumption of identical meals for 3 days, and collected feces were analyzed through terminal restriction fragment length polymorphism. The obtained operational taxonomic units and smoking habits of subjects were analyzed by a data mining software. The constructed decision tree was able to identify explicitly the groups of smokers and nonsmokers. In particular, 4 smokers, who smoked 20 cigarettes/day, i.e., heavy smokers, were gathered in the same group of the decision tree and were clearly identified. Related operational taxonomic unit were traced to understand the species of bacteria, but all were found to be uncultured bacteria.

Journal

• Bioscience of Microbiota, Food and Health

  Bioscience of Microbiota, Food and Health 32 (2), 77-80, 2013

  BMFH Press

Keywords

• human intestinal microbiota
• restriction enzyme
• operational taxonomic unit
• smoking habit
• heavy smoker
• data mining analysis
• decision tree

Details

• CRID: 1390001205410001792
• NII Article ID: 10031166713
• NII Book ID: AA12588288
• DOI: 10.12938/bmfh.32.77
• ISSN: 21863342
• Web Site: https://www.jstage.jst.go.jp/article/bmfh/32/2/32_77/_pdf
• Web Site: https://search.jamas.or.jp/link/ui/2014180835
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed