Watch the Dallas Symposium LIVE, and fundraiser auction
Ticket proceeds support mindat.org! - click here...
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Eraslan, Gökcen, Simon, Lukas M., Mircea, Maria, Mueller, Nikola S., Theis, Fabian J. (2019) Single-cell RNA-seq denoising using a deep count autoencoder. Nature Communications, 10. doi:10.1038/s41467-018-07931-2

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleSingle-cell RNA-seq denoising using a deep count autoencoder
JournalNature Communications
AuthorsEraslan, GökcenAuthor
Simon, Lukas M.Author
Mircea, MariaAuthor
Mueller, Nikola S.Author
Theis, Fabian J.Author
Year2019 (December)Volume10
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1038/s41467-018-07931-2Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID6094853Long-form Identifiermindat:1:5:6094853:1
GUID0
Full ReferenceEraslan, Gökcen, Simon, Lukas M., Mircea, Maria, Mueller, Nikola S., Theis, Fabian J. (2019) Single-cell RNA-seq denoising using a deep count autoencoder. Nature Communications, 10. doi:10.1038/s41467-018-07931-2
Plain TextEraslan, Gökcen, Simon, Lukas M., Mircea, Maria, Mueller, Nikola S., Theis, Fabian J. (2019) Single-cell RNA-seq denoising using a deep count autoencoder. Nature Communications, 10. doi:10.1038/s41467-018-07931-2
In(2019) Nature Communications Vol. 10. Springer Science and Business Media LLC

See Also

These are possibly similar items as determined by title/reference text matching only.

Büttner, Maren, Miao, Zhichao, Wolf, F. Alexander, Teichmann, Sarah A., Theis, Fabian J. (2019) A test metric for assessing single-cell RNA-seq batch correction. Nature Methods, 16 (1). 43-49 doi:10.1038/s41592-018-0254-1
Danese, Anna, Richter, Maria L., Chaichoompu, Kridsadakorn, Fischer, David S., Theis, Fabian J., Colomé-Tatché, Maria (2021) EpiScanpy: integrated single-cell epigenomic analysis. Nature Communications, 12 (1) doi:10.1038/s41467-021-25131-3
Angelidis, Ilias, Simon, Lukas M., Fernandez, Isis E., Strunz, Maximilian, Mayr, Christoph H., Greiffo, Flavia R., Tsitsiridis, George, Ansari, Meshal, Graf, Elisabeth, Strom, Tim-Matthias, Nagendran, Monica, Desai, Tushar, Eickelberg, Oliver, Mann, Matthias, Theis, Fabian J., Schiller, Herbert B. (2019) An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics. Nature Communications, 10. doi:10.1038/s41467-019-08831-9
Vieth, Beate, Parekh, Swati, Ziegenhain, Christoph, Enard, Wolfgang, Hellmann, Ines (2019) A systematic evaluation of single cell RNA-seq analysis pipelines. Nature Communications, 10. doi:10.1038/s41467-019-12266-7
Poirion, Olivier, Zhu, Xun, Ching, Travers, Garmire, Lana X. (2018) Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage. Nature Communications, 9. doi:10.1038/s41467-018-07170-5
Alavi, Amir, Ruffalo, Matthew, Parvangada, Aiyappa, Huang, Zhilin, Bar-Joseph, Ziv (2018) A web server for comparative analysis of single-cell RNA-seq data. Nature Communications, 9. doi:10.1038/s41467-018-07165-2
Li, Wei Vivian, Li, Jingyi Jessica (2018) An accurate and robust imputation method scImpute for single-cell RNA-seq data. Nature Communications, 9. doi:10.1038/s41467-018-03405-7
Risso, Davide, Perraudeau, Fanny, Gribkova, Svetlana, Dudoit, Sandrine, Vert, Jean-Philippe (2019) Publisher Correction: A general and flexible method for signal extraction from single-cell RNA-seq data. Nature Communications, 10. doi:10.1038/s41467-019-08614-2
Qiu, Peng (2020) Embracing the dropouts in single-cell RNA-seq analysis. Nature Communications, 11. doi:10.1038/s41467-020-14976-9
Ding, Jiarui, Regev, Aviv (2021) Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces. Nature Communications, 12 (1) doi:10.1038/s41467-021-22851-4
Yan, Guanao, Song, Dongyuan, Li, Jingyi Jessica (2023) scReadSim: a single-cell RNA-seq and ATAC-seq read simulator. Nature Communications, 14 (1) doi:10.1038/s41467-023-43162-w
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 20, 2025 01:44:16
Go to top of page