Mining influential genes based on deep learning

Mining influential genes based on deep learning

Background: Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-expanding gene expression profile, a new, low-cost, high-throughput reduced repr...

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Bibliographic Details
Main Authors: Chen, Y. (Author), Fang, J. (Author), Kong, L. (Author), Li, Z. (Author), Pian, C. (Author), Xu, F. (Author), Xu, M. (Author), Zhang, L. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
AutoEncoder
Computational framework
Correlation methods
Data-driven approach
Deep learning
Deep Learning
DeepLIFT
Explosives
Functional connection
Gene expression
Gene expression profiles
gene expression profiling
Gene expression profiling
Gene Expression Profiling
genome
Genome
genomics
Genomics
Landmark genes
Non-linear relationships
Pearson correlation coefficients
Reduced representation
transcriptome
Transcriptome
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