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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
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| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/12/7/1498 |