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mSRFR: a machine learning model using microalgal signature features for ncRNA classification.
Anuntakarun, Songtham; Lertampaiporn, Supatcha; Laomettachit, Teeraphan; Wattanapornprom, Warin; Ruengjitchatchawalya, Marasri.
Affiliation
  • Anuntakarun S; Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (KMUTT), Bangkok, 10150, Thailand.
  • Lertampaiporn S; School of Information Technology, KMUTT, Bang Mod, Thung Khru, Bangkok, 10140, Thailand.
  • Laomettachit T; Biochemical Engineering and Systems Biology Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency at King Mongkut's University of Technology Thonburi, Bang Khun Thian, Bangkok, 10150, Thailand.
  • Wattanapornprom W; Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (KMUTT), Bangkok, 10150, Thailand.
  • Ruengjitchatchawalya M; Department of Mathematics, Faculty of Science, KMUTT, Bangkok, 10140, Thailand.
BioData Min ; 15(1): 8, 2022 Mar 21.
Article in En | MEDLINE | ID: mdl-35313925
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: BioData Min Year: 2022 Document type: Article Affiliation country: Thailand Country of publication: United kingdom
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: BioData Min Year: 2022 Document type: Article Affiliation country: Thailand Country of publication: United kingdom