A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model

Background: Orphan gene play an important role in the environmental stresses of many species and their identification is a critical step to understand biological functions. Moso bamboo has high ecological, economic and cultural value. Studies have shown that the growth of moso bamboo is influenced b...

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Bibliographic Details
Main Authors:	Gao, Q. (Author), Jin, X. (Author), Li, S. (Author), Wang, L. (Author), Xuan, J. (Author), Yao, C. (Author), Zhang, X. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2022
Subjects:	amino acid sequence Amino-acids article Bamboo Coefficient values controlled study Convolution convolutional neural network Convolutional neural network Convolutional neural networks correlation coefficient Correlation coefficient deep learning Deep learning gated recurrent unit network gene identification Genes human Moso bamboo Neural-networks nonhuman Orphan gene Orphan genes Phyllostachys recurrent neural network Recurrent neural networks short term memory Transformer modeling Transformer neural network
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A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model

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