What is being modeled?
Identifying cell fate transition from scRNA-seq data with applications to EMT
Description & purpose of resource
An unsupervised learning of single-cell transcriptomic data for identification of individual cells making transition between all cell states, and inference of genes that mark transitions.
1 - 103 s
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
Link to Resource Credibility Assessment
Key publications (e.g. describing or using resource)
Sha, Yutong, Shuxiong Wang, Peijie Zhou, and Qing Nie. "Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data." Nucleic acids research 48, no. 17 (2020): 9505-9520.
DOI link to publication describing this resource
Link to resource
Qing Nie (PI)
PI contact information
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