Cargando…
Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion
High-throughput spatial-transcriptomics RNA sequencing (sptRNA-seq) based on in-situ capturing technologies has recently been developed to spatially resolve transcriptome-wide mRNA expressions mapped to the captured locations in a tissue sample. Due to the low RNA capture efficiency by in-situ captu...
Autores principales: | Li, Zhuliu, Song, Tianci, Yong, Jeongsik, Kuang, Rui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055040/ https://www.ncbi.nlm.nih.gov/pubmed/33826608 http://dx.doi.org/10.1371/journal.pcbi.1008218 |
Ejemplares similares
-
Traffic Speed Data Imputation Method Based on Tensor Completion
por: Ran, Bin, et al.
Publicado: (2015) -
Completeness and regularity of generalized fuzzy graphs
por: Samanta, Sovan, et al.
Publicado: (2016) -
Network-based machine learning and graph theory algorithms for precision oncology
por: Zhang, Wei, et al.
Publicado: (2017) -
Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder
por: Dong, Kangning, et al.
Publicado: (2022) -
Revealing Tissue Heterogeneity and Spatial Dark Genes from Spatially Resolved Transcriptomics by Multiview Graph Networks
por: Li, Ying, et al.
Publicado: (2023)