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Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data
BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the data. A class of neural networks, namely autoencoders, has been useful for denois...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6615267/ https://ncbi.nlm.nih.gov/pubmed/31286861 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-2952-9 |
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