CodonBERT: a BERT-based architecture tailored for codon optimization using the cross-attention mechanism.

ABSTRACT:

Motivation

Due to the varying delivery methods of mRNA vaccines, codon optimization plays a critical role in vaccine design to improve the stability and expression of proteins in specific tissues. Considering the many-to-one relationship between synonymous codons and amino acids, the number of mRNA sequences encoding the same amino acid sequence could be enormous. Finding stable and highly expressed mRNA sequences from the vast sequence space using in silico methods can generally be viewed as a path-search problem or a machine translation problem. However, current deep learning-based methods inspired by machine translation may have some limitations, such as recurrent neural networks, which have a weak ability to capture the long-term dependencies of codon preferences.

Results

SUBMITTER: Ren Z 

PROVIDER: S-EPMC11226863 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature