Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data

Savvas Kinalis; Finn Cilius Nielsen; Ole Winther; Frederik Otzen Bagger

doi:10.1186/s12859-019-2952-9

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data

Savvas Kinalis, Finn Cilius Nielsen, Ole Winther, Frederik Otzen Bagger

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

22 Citationer (Scopus)

282 Downloads (Pure)

Originalsprog	Engelsk
Artikelnummer	379
Tidsskrift	BMC Bioinformatics
Vol/bind	20
Antal sider	9
ISSN	1471-2105
DOI	https://doi.org/10.1186/s12859-019-2952-9
Status	Udgivet - 2019

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10.1186/s12859-019-2952-9Licens: CC BY

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing dataForlagets udgivne version, 2,12 MBLicens: CC BY

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@article{2bfca381b48b450e8ca8dcd8e89d2045,

title = "Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data",

keywords = "Interpretable machine learning, Deep learning, Neural networks, Manifold learning, Expression profiles, Single-cell RNA-sequencing, Gene set enrichment analysis, Functional analysis, Biological pathway analysis",

author = "Savvas Kinalis and Nielsen, {Finn Cilius} and Ole Winther and Bagger, {Frederik Otzen}",

year = "2019",

doi = "10.1186/s12859-019-2952-9",

language = "English",

volume = "20",

journal = "BMC Bioinformatics",

issn = "1471-2105",

publisher = "BioMed Central Ltd.",

}

TY - JOUR

T1 - Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data

AU - Kinalis, Savvas

AU - Nielsen, Finn Cilius

AU - Winther, Ole

AU - Bagger, Frederik Otzen

PY - 2019

Y1 - 2019

KW - Interpretable machine learning

KW - Deep learning

KW - Neural networks

KW - Manifold learning

KW - Expression profiles

KW - Single-cell RNA-sequencing

KW - Gene set enrichment analysis

KW - Functional analysis

KW - Biological pathway analysis

U2 - 10.1186/s12859-019-2952-9

DO - 10.1186/s12859-019-2952-9

M3 - Journal article

C2 - 31286861

SN - 1471-2105

VL - 20

JO - BMC Bioinformatics

JF - BMC Bioinformatics

M1 - 379

ER -