A BERT-based approach for identifying anti-inflammatory peptides using sequence information.

ABSTRACT: The use of anti-inflammatory peptides (AIPs) as an alternative therapeutic approach for inflammatory diseases holds great research significance. Due to the high cost and difficulty in identifying AIPs with experimental methods, the discovery and design of peptides by computational methods before the experimental stage have become promising technology. In this study, we present BertAIP, a bidirectional encoder representation from transformers (BERT)-based method for predicting AIPs directly from their amino acid sequence without using any other information. BertAIP implements a BERT model to extract features of a protein, and uses a fully connected feed-forward network for AIP classification. It was constructed and evaluated using the AIP datasets that were reconstructed from the latest Imm

SUBMITTER: Xu T 

PROVIDER: S-EPMC11234020 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature