Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes
Global patterns of gene transcription can be represented with reduced dimensionality. Here, the authors devise a method called Tradict that learns and uses 100 marker genes to predict transcriptome-wide pathway expression levels and patterns that reflect cell activity and state.
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2017-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/ncomms15309 |
| _version_ | 1818977671238909952 |
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| author | Surojit Biswas Konstantin Kerner Paulo José Pereira Lima Teixeira Jeffery L. Dangl Vladimir Jojic Philip A. Wigge |
| author_facet | Surojit Biswas Konstantin Kerner Paulo José Pereira Lima Teixeira Jeffery L. Dangl Vladimir Jojic Philip A. Wigge |
| author_sort | Surojit Biswas |
| collection | DOAJ |
| description | Global patterns of gene transcription can be represented with reduced dimensionality. Here, the authors devise a method called Tradict that learns and uses 100 marker genes to predict transcriptome-wide pathway expression levels and patterns that reflect cell activity and state. |
| first_indexed | 2024-12-20T16:31:27Z |
| format | Article |
| id | doaj.art-ce737e4cc0ea42049b5f81c9b37826b7 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-20T16:31:27Z |
| publishDate | 2017-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-ce737e4cc0ea42049b5f81c9b37826b72022-12-21T19:33:16ZengNature PortfolioNature Communications2041-17232017-05-018111010.1038/ncomms15309Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genesSurojit Biswas0Konstantin Kerner1Paulo José Pereira Lima Teixeira2Jeffery L. Dangl3Vladimir Jojic4Philip A. Wigge5Department of Biomedical Informatics, Harvard Medical SchoolBotanical Institute, Biocenter, University of CologneHoward Hughes Medical Institute, University of North Carolina at Chapel HillHoward Hughes Medical Institute, University of North Carolina at Chapel HillDepartment of Computer Science, University of North Carolina at Chapel HillSainsbury Laboratory, University of CambridgeGlobal patterns of gene transcription can be represented with reduced dimensionality. Here, the authors devise a method called Tradict that learns and uses 100 marker genes to predict transcriptome-wide pathway expression levels and patterns that reflect cell activity and state.https://doi.org/10.1038/ncomms15309 |
| spellingShingle | Surojit Biswas Konstantin Kerner Paulo José Pereira Lima Teixeira Jeffery L. Dangl Vladimir Jojic Philip A. Wigge Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes Nature Communications |
| title | Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| title_full | Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| title_fullStr | Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| title_full_unstemmed | Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| title_short | Tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| title_sort | tradict enables accurate prediction of eukaryotic transcriptional states from 100 marker genes |
| url | https://doi.org/10.1038/ncomms15309 |
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