Your browser doesn't support javascript.
loading
Colony Fingerprint-Based Discrimination of Staphylococcus species with Machine Learning Approaches.
Maeda, Yoshiaki; Sugiyama, Yui; Kogiso, Atsushi; Lim, Tae-Kyu; Harada, Manabu; Yoshino, Tomoko; Matsunaga, Tadashi; Tanaka, Tsuyoshi.
Afiliação
  • Maeda Y; Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei, Tokyo 184-8588, Japan. y_maeda@cc.tuat.ac.jp.
  • Sugiyama Y; Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei, Tokyo 184-8588, Japan. y-sugiyama@st.go.tuat.ac.jp.
  • Kogiso A; Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei, Tokyo 184-8588, Japan. akogiso9305@gmail.com.
  • Lim TK; Malcom Co., Ltd., 4-15-10, Honmachi, Shibuya-ku, Tokyo 151-0071, Japan. lim@malcom.co.jp.
  • Harada M; Malcom Co., Ltd., 4-15-10, Honmachi, Shibuya-ku, Tokyo 151-0071, Japan. harada@malcom.co.jp.
  • Yoshino T; Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei, Tokyo 184-8588, Japan. y-tomoko@cc.tuat.ac.jp.
  • Matsunaga T; Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei, Tokyo 184-8588, Japan. tmatsuna@cc.tuat.ac.jp.
  • Tanaka T; Waseda Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. tmatsuna@cc.tuat.ac.jp.
Sensors (Basel) ; 18(9)2018 Aug 24.
Article em En | MEDLINE | ID: mdl-30149555
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article