TIVelo: RNA velocity estimation leveraging cluster-level trajectory inference
Abstract RNA velocity inference is a valuable tool for understanding cell development, differentiation, and disease progression. However, existing RNA velocity inference methods typically rely on explicit assumptions of ordinary differential equations (ODE), which prohibits them from capturing compl...
Saved in:
| Main Authors: | Muyang Ge, Jishuai Miao, Ji Qi, Xiaocheng Zhou, Zhixiang Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61628-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
spVelo: RNA velocity inference for multi-batch spatial transcriptomics data
by: Wenxin Long, et al.
Published: (2025-08-01) -
GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells
by: Yuhao Chen, et al.
Published: (2025-08-01) -
Experimental Validation of Positioning Control for an X–Y Table Using S-Curve Velocity Trajectory
by: Hsiu-Ming Wu, et al.
Published: (2025-04-01) -
Energy-Efficient UAV Trajectory Design and Velocity Control for Visual Coverage of Terrestrial Regions
by: Hengchao Li, et al.
Published: (2025-04-01) -
Personalized trajectory inference framework integrating driving behavior recognition and temporal dependency learning.
by: Jinhao Yang, et al.
Published: (2025-01-01)