An Interpretable Double-Scale Attention Model for Enzyme Protein Class Prediction Based on Transformer Encoders and Multi-Scale Convolutions

An Interpretable Double-Scale Attention Model for Enzyme Protein Class Prediction Based on Transformer Encoders and Multi-Scale Convolutions

Background Classification and annotation of enzyme proteins are fundamental for enzyme research on biological metabolism. Enzyme Commission (EC) numbers provide a standard for hierarchical enzyme class prediction, on which several computational methods have been proposed. However, most of these meth...

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Bibliographic Details
Main Authors: Ken Lin, Xiongwen Quan, Chen Jin, Zhuangwei Shi, Jinglong Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Genetics
Subjects:
enzyme class prediction
self-attention
multi-scale convolutions
double-scale attention
feature agreement
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2022.885627/full

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