Content posted to this wiki are contributions made by the IMAG research community.
Any questions or concerns should be directed to the individual authors. Full disclaimer statement found here

scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data

What is being modeled?
Cellular trajectories, transition probabilities, energy landscape.
Description & purpose of resource

scEpath is an approach that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories.

Spatial scales
Temporal scales
1 - 103 s
weeks to months
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
Key publications (e.g. describing or using resource)

Suoqin Jin, Adam L. MacLean, Tao Peng, Qing Nie. scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data. Bioinformatics. 2018 Jun 15;34(12):2077-2086. doi: 10.1093/bioinformatics/bty058.

Qing Nie
PI contact information
Table sorting checkbox