eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells

eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio–temporal architectures of cells

Abstract Background Bioinformatics capability to analyze spatio–temporal dynamics of gene expression is essential in understanding animal development. Animal cells are spatially organized as functional tissues where cellular gene expression data contain information that governs morphogenesis during...

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Bibliographic Details
Main Authors: Tomoya Mori, Toshiro Takase, Kuan-Chun Lan, Junko Yamane, Cantas Alev, Azuma Kimura, Kenji Osafune, Jun K. Yamashita, Tatsuya Akutsu, Hiroaki Kitano, Wataru Fujibuchi
Format: Article
Language:English
Published: BMC 2023-06-01
Series:BMC Bioinformatics
Subjects:
Spatio–temporal tissue reconstruction
Cellular organization
Spatial discriminator gene
Self-organizing map clustering
Markov chain Monte Carlo optimization
Developmental trajectory
Online Access:https://doi.org/10.1186/s12859-023-05355-4

Internet

https://doi.org/10.1186/s12859-023-05355-4

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