A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides

A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides

As major components of spider venoms, neurotoxic peptides exhibit structural diversity, target specificity, and have great pharmaceutical potential. Deep learning may be an alternative to the laborious and time-consuming methods for identifying these peptides. However, the major hurdle in developing...

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Bibliographic Details
Main Authors: Byungjo Lee, Min Kyoung Shin, In-Wook Hwang, Junghyun Jung, Yu Jeong Shim, Go Woon Kim, Seung Tae Kim, Wonhee Jang, Jung-Suk Sung
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:International Journal of Molecular Sciences
Subjects:
deep learning
data augmentation
convolutional neural network
neurotoxic peptide prediction
spider transcriptome
Online Access:https://www.mdpi.com/1422-0067/22/22/12291

Internet

https://www.mdpi.com/1422-0067/22/22/12291

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