iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides

Author:

Charoenkwan Phasit1,Yana Janchai2,Nantasenamat Chanin3ORCID,Hasan Md. Mehedi4,Shoombuatong Watshara3ORCID

Affiliation:

1. Modern Management and Information Technology, College of Arts, Media and Technology, Chiang Mai University, Chiang Mai 50200, Thailand

2. Department of Chemistry, Faculty of Science and Technology, Chiang Mai Rajabhat University, Chiang Mai 50300, Thailand

3. Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

4. Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

Funder

Chiang Mai University

College of Arts, Media and Technology, Chiang Mai University

Office of the Higher Education Commission

Thailand Research Fund

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

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