Technical Aspects of Nominal Partitions on Accuracy of Data Mining Classification of Intestinal Microbiota — Comparison between 7 Restriction Enzymes
Author:
Affiliation:
1. Riken, 2–1 Hirosawa, Wako, Saitama 351-0198, Japan
2. Miyagi University, 2–2–1 Hatadate, Taihaku-ku, Sendai City, Miyagi 982-0215, Japan
3. Yokohama Rosai Hospital, JLHWO, Kozukue-cho, Kohoku-ku, Yokohama 222-0036, Japan
Publisher
BMFH Press
Subject
Gastroenterology,Applied Microbiology and Biotechnology,Immunology,Microbiology,Food Science
Link
https://www.jstage.jst.go.jp/article/bmfh/33/3/33_2013-019/_pdf
Reference15 articles.
1. 1. Kobayashi T, Fujiwara K. 2013. Identification of heavy smokers through their intestinal microbiota by data mining analysis. Biosci Microb Food Health 32: 77–80.
2. 2. Kobayashi T, Jin J, Kibe R, Toyama M, Tanaka Y, Benno Y, Fujiwara K, Shimakawa M, Maruo T, Toda T, Matsuda I, Tagami H, Matsumoto M, Seo G, Sato N, Chounan O, Benno Y. 2013. Identification of human intestinal microbiota of 92 men by Data Mining for 5 characteristics, i.e. ages, BMI, smoking habit, cessation period of previous smokers and drinking habit. Biosci Microb Food Health 32: 129–137.
3. 3. Kobayashi T, Fujiwara K. 2013. Comparison of the accuracy and mechanism of Data mining identification of the intestinal microbiota with 7 restriction enzymes. Biosci Microb Food Health 32: 139–148.
4. 4. Jin JS, Toyama M, Kibe R, Tanaka Y, Benno Y, Kobayashi T, Shimakawa M, Maruo T, Toda T, Matsuda I, Tagami H, Matsumoto M, Seo G, Sato N, Chounan O, Benno Y. 2013. Analysis of the human intestinal microbiota from 92 volunteers after ingestion of identical meals. Benef Microbes 4: 187–193.
5. 5. Andoh A, Kuzuoka H, Tsujikawa T, Nakamura S, Hirai F, Suzuki Y, Matsui T, Fujiyama Y, Matsumoto T. 2012. Multicenter analysis of fecal microbiota profiles in Japanese patients with Crohn’s disease. J Gastroenterol 47: 1298–1307.
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1. Numerical analyses of intestinal microbiota by data mining;Journal of Clinical Biochemistry and Nutrition;2018
2. Characterization of gut microbiota profiles in coronary artery disease patients using data mining analysis of terminal restriction fragment length polymorphism: gut microbiota could be a diagnostic marker of coronary artery disease;Heart and Vessels;2016-04-28
3. Use of T-RFLP and seven restriction enzymes to compare the faecal microbiota of obese and lean Japanese healthy men;Beneficial Microbes;2015-10-15
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