Different Recognition of Protein Features Depending on Deep Learning Models: A Case Study of Aromatic Decarboxylase UbiD

Different Recognition of Protein Features Depending on Deep Learning Models: A Case Study of Aromatic Decarboxylase UbiD

The number of unannotated protein sequences is explosively increasing due to genome sequence technology. A more comprehensive understanding of protein functions for protein annotation requires the discovery of new features that cannot be captured from conventional methods. Deep learning can extract...

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Bibliographic Details
Main Authors: Naoki Watanabe, Yuki Kuriya, Masahiro Murata, Masaki Yamamoto, Masayuki Shimizu, Michihiro Araki
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Biology
Subjects:
deep learning
protein feature
feature extraction
explainable artificial intelligence
integrated gradients
protein annotation
Online Access:https://www.mdpi.com/2079-7737/12/6/795

Internet

https://www.mdpi.com/2079-7737/12/6/795

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