IUP-BERT: Identification of Umami Peptides Based on BERT Features.

ABSTRACT: Umami is an important widely-used taste component of food seasoning. Umami peptides are specific structural peptides endowing foods with a favorable umami taste. Laboratory approaches used to identify umami peptides are time-consuming and labor-intensive, which are not feasible for rapid screening. Here, we developed a novel peptide sequence-based umami peptide predictor, namely iUP-BERT, which was based on the deep learning pretrained neural network feature extraction method. After optimization, a single deep representation learning feature encoding method (BERT: bidirectional encoder representations from transformer) in conjugation with the synthetic minority over-sampling technique (SMOTE) and support vector machine (SVM) methods was adopted for model creation to generate predicted prob

SUBMITTER: Jiang L 

PROVIDER: S-EPMC9689418 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature