The Human Cell Atlas: from vision to reality
By O. Rozenblatt-Rosen, Michael J. T. Stubbington, Aviv Regev, Sarah A. Teichmann. Nature, 2017
600 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Biophysics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/e92116407430853dad39c62f4643438f69202466
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
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- Aaron T. L. Lun
- Manolis Kellis
- Charlotte Soneson
- Paul Flicek
- Martin T. Morgan
- Daniel R. Zerbino
- Stephanie C. Hicks
- Benedict Paten
Citations in the corpus
- Ensembl 2023 (2022, methodology): “The Ensembl/GENCODE human reference annotation (15) is used globally by major projects and consortia including the NHGRI-EBI GWAS Catalog (16), UK BioBank (17), ICGC/TCGA (18), gnomAD (19) and the Human Cell Atlas (20), which demands that the annotations reflect the latest scientific understanding a”
- Deep learning for cellular image analysis (2019, unknown): “We anticipate that deep learning will be critical for development of the Human Cell Atlas 107,108 , as image analysis is common to all spatial transcrip-tomics and proteomics experiments.”
- The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution (2020, unknown): “HTAN strives to provide compatibility with other relevant platforms, such as the Human Cell Atlas (HCA) Data Coordination Platform and the Human Biomolecular Atlas Program (HuBMAP) High-Performance Integrated Virtual Environment portal.”
- SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data (2018, unknown): “Moreover, large-scale efforts to create a ”Human Cell Atlas” critically depend on the accuracy and cellular specificity of the transcriptional readout produced by droplet-based scRNA-seq [9, 10].”
- Orchestrating single-cell analysis with Bioconductor (2019, background): “…the increased scale of the number of observations (that is, cells) that are assayed in large compendiums such as those from the Human Cell Atlas 21,22 and the Mouse Cell Atlas 23 ; and (2) the increased sparsity of the data due to biological fluctuations in the measured traits or limited…”
- GENCODE 2021 (2020, methodology): “We also included genes curated by UniProt (4) and the Human Cell Atlas project (16) as well as interferonstimulated genes with known antiviral activity (17).”