Supervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images

Supervised and Unsupervised End-to-End Deep Learning for Gene Ontology Classification of Neural In Situ Hybridization Images

In recent years, large datasets of high-resolution mammalian neural images have become available, which has prompted active research on the analysis of gene expression data. Traditional image processing methods are typically applied for learning functional representations of genes, based on their ex...

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Bibliographic Details
Main Authors: Ido Cohen, Eli (Omid) David, Nathan S. Netanyahu
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Entropy
Subjects:
deep learning
convolutional neural networks
denoising autoencoders
ISH images
gene categorization
Online Access:https://www.mdpi.com/1099-4300/21/3/221

Internet

https://www.mdpi.com/1099-4300/21/3/221

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