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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Detalles Bibliográficos
Autores principales: Jiang, Jici, Li, Jiayu, Li, Junxian, Pei, Hongdi, Li, Mingxin, Zou, Quan, Lv, Zhibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094688/
https://www.ncbi.nlm.nih.gov/pubmed/37048319
http://dx.doi.org/10.3390/foods12071498

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10094688/
https://www.ncbi.nlm.nih.gov/pubmed/37048319
http://dx.doi.org/10.3390/foods12071498

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