A Machine Learning Method to Identify Umami Peptide Sequences by Using Multiplicative LSTM Embedded Features

A Machine Learning Method to Identify Umami Peptide Sequences by Using Multiplicative LSTM Embedded Features

Umami peptides enhance the umami taste of food and have good food processing properties, nutritional value, and numerous potential applications. Wet testing for the identification of umami peptides is a time-consuming and expensive process. Here, we report the iUmami-DRLF that uses a logistic regres...

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Bibliographic Details
Main Authors: Jici Jiang, Jiayu Li, Junxian Li, Hongdi Pei, Mingxin Li, Quan Zou, Zhibin Lv
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Foods
Subjects:
umami peptide
deep representation learning
SMOTE
ANOVA
light gradient boosting
mutual information
Online Access:https://www.mdpi.com/2304-8158/12/7/1498

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