Cargando…
Leveraging the Cell Ontology to classify unseen cell types
Single cell technologies are rapidly generating large amounts of data that enables us to understand biological systems at single-cell resolution. However, joint analysis of datasets generated by independent labs remains challenging due to a lack of consistent terminology to describe cell types. Here...
Autores principales: | Wang, Sheng, Pisco, Angela Oliveira, McGeever, Aaron, Brbic, Maria, Zitnik, Marinka, Darmanis, Spyros, Leskovec, Jure, Karkanias, Jim, Altman, Russ B. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455606/ https://www.ncbi.nlm.nih.gov/pubmed/34548483 http://dx.doi.org/10.1038/s41467-021-25725-x |
Ejemplares similares
-
Predicting multicellular function through multi-layer tissue networks
por: Zitnik, Marinka, et al.
Publicado: (2017) -
Prioritizing network communities
por: Zitnik, Marinka, et al.
Publicado: (2018) -
Modeling polypharmacy side effects with graph convolutional networks
por: Zitnik, Marinka, et al.
Publicado: (2018) -
Identification of disease treatment mechanisms through the multiscale interactome
por: Ruiz, Camilo, et al.
Publicado: (2021) -
Evolution of resilience in protein interactomes across the tree of life
por: Zitnik, Marinka, et al.
Publicado: (2019)