Statistical and machine learning methods for spatially resolved transcriptomics data analysis
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1474-760X
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Statistical and machine learning methods for spatially resolved transcriptomics data analysis ; volume:23 ; number:1 ; day:25 ; month:3 ; year:2022 ; pages:1-23 ; date:12.2022
Genome biology ; 23, Heft 1 (25.3.2022), 1-23, 12.2022
- Creator
-
Zeng, Zexian
Li, Yawei
Li, Yiming
Luo, Yuan
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s13059-022-02653-7
- URN
-
urn:nbn:de:101:1-2022061620353823710542
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:36 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zeng, Zexian
- Li, Yawei
- Li, Yiming
- Luo, Yuan
- SpringerLink (Online service)
Other Objects (12)
"Paralleldeposition" of Size-Selected Clusters
Unsupervised phenotyping of sepsis using nonnegative matrix factorization of temporal trends from a multivariate panel of physiological measurements
Contrasting rule and machine learning based digital self triage systems in the USA
STdGCN: spatial transcriptomic cell-type deconvolution using graph convolutional networks
Bilobalide modulates serotonin-controlled behaviors in the nematode Caenorhabditis elegans
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
Efficient Genomic Interval Queries Using Augmented Range Trees
Seismic stability evaluation of embankment slope based on catastrophe theory
Antidepressants are a rational complementary therapy for the treatment of Alzheimer's disease
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments
Spatially Resolved Transcriptomics Technology Facilitates Cancer Research
"Paralleldeposition" of Size-Selected Clusters
Unsupervised phenotyping of sepsis using nonnegative matrix factorization of temporal trends from a multivariate panel of physiological measurements
Contrasting rule and machine learning based digital self triage systems in the USA
STdGCN: spatial transcriptomic cell-type deconvolution using graph convolutional networks
Bilobalide modulates serotonin-controlled behaviors in the nematode Caenorhabditis elegans
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
Efficient Genomic Interval Queries Using Augmented Range Trees
Seismic stability evaluation of embankment slope based on catastrophe theory
Antidepressants are a rational complementary therapy for the treatment of Alzheimer's disease
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments
Spatially Resolved Transcriptomics Technology Facilitates Cancer Research
"Paralleldeposition" of Size-Selected Clusters
Unsupervised phenotyping of sepsis using nonnegative matrix factorization of temporal trends from a multivariate panel of physiological measurements
Contrasting rule and machine learning based digital self triage systems in the USA
STdGCN: spatial transcriptomic cell-type deconvolution using graph convolutional networks
Bilobalide modulates serotonin-controlled behaviors in the nematode Caenorhabditis elegans
Clinical text classification with rule-based features and knowledge-guided convolutional neural networks
Efficient Genomic Interval Queries Using Augmented Range Trees
Seismic stability evaluation of embankment slope based on catastrophe theory
Antidepressants are a rational complementary therapy for the treatment of Alzheimer's disease
Spatially resolved transcriptomics in immersive environments
Spatially resolved transcriptomics in immersive environments