UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning

Umami ingredients have been identified as important factors in food seasoning and production. Traditional experimental methods for characterizing peptides exhibiting umami sensory properties (umami peptides) are time-consuming, laborious, and costly. As a result, it is preferable to develop computat...

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Bibliographic Details
Main Authors: Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:International Journal of Molecular Sciences
Subjects:
umami peptide
sequence analysis
bioinformatics
machine learning
feature representation learning
Online Access:https://www.mdpi.com/1422-0067/22/23/13124

Internet

https://www.mdpi.com/1422-0067/22/23/13124

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