Cargando…
MetaTiME integrates single-cell gene expression to characterize the meta-components of the tumor immune microenvironment
Recent advances in single-cell RNA sequencing have shown heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can indicate common cell types and states in the tumor microenvironment (TME). We develop a...
Autores principales: | Zhang, Yi, Xiang, Guanjue, Jiang, Alva Yijia, Lynch, Allen, Zeng, Zexian, Wang, Chenfei, Zhang, Wubing, Fan, Jingyu, Kang, Jiajinlong, Gu, Shengqing Stan, Wan, Changxin, Zhang, Boning, Liu, X. Shirley, Brown, Myles, Meyer, Clifford A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164163/ https://www.ncbi.nlm.nih.gov/pubmed/37149682 http://dx.doi.org/10.1038/s41467-023-38333-8 |
Ejemplares similares
-
Machine learning on syngeneic mouse tumor profiles to model clinical immunotherapy response
por: Zeng, Zexian, et al.
Publicado: (2022) -
Machine Learning Modeling of Protein-intrinsic Features Predicts Tractability of Targeted Protein Degradation
por: Zhang, Wubing, et al.
Publicado: (2022) -
TISMO: syngeneic mouse tumor database to model tumor immunity and immunotherapy response
por: Zeng, Zexian, et al.
Publicado: (2021) -
Clonal tracing reveals diverse patterns of response to immune checkpoint blockade
por: Gu, Shengqing Stan, et al.
Publicado: (2020) -
Large-scale public data reuse to model immunotherapy response and resistance
por: Fu, Jingxin, et al.
Publicado: (2020)