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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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Bibliografske podrobnosti
izdano v:BMC Bioinformatics
Main Authors: Kinalis, Savvas, Nielsen, Finn Cilius, Winther, Ole, Bagger, Frederik Otzen
Format: Artigo
Jezik:Inglês
Izdano: BioMed Central 2019
Teme:
Online dostop: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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