ArticleiScience2022
hECA: The cell-centric assembly of a cell atlas.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Application of human induced pluripotent stem cells for tissue modeling and therapy: are we on track?Stem cells (Dayton, Ohio) · 2026Review
- Cross-dataset annotation harmonization for cell-type hierarchy construction.Bioinformatics (Oxford, England) · 2026Article
- Benchmarking AI scientists for omics data-driven biological discovery.Bioinformatics (Oxford, England) · 2026Article
- hECA v2.0: an AI-ready ensemble cell atlas of single-cell RNA and ATAC sequencing data.Scientific data · 2025Article
- Optimal marker genes forGenome research · 2025Article
- A comparative review of single-cell atlases: mapping cellular diversity across species and tissues.Cellular and molecular life sciences : CMLS · 2025Review
- Nicheformer: a foundation model for single-cell and spatial omics.Nature methods · 2025Article
- Single-cell foundation models: bringing artificial intelligence into cell biology.Experimental & molecular medicine · 2025Review
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- Single-cell transcriptome of mouse hippocampus identifies neural precursor-like cells, and reveals IL15Rα knock out-mediated neuron remodeling.BMC genomics · 2025Article
- uHAF: a unified hierarchical annotation framework for cell type standardization and harmonization.Bioinformatics (Oxford, England) · 2025Article
- A NovelInternational journal of molecular sciences · 2025Article
- scTML: a pan-cancer single-cell landscape of multiple mutation types.Nucleic acids research · 2025Article
- General-purpose pre-trained large cellular models for single-cell transcriptomics.National science review · 2024Article
- starTracer is an accelerated approach for precise marker gene identification in single-cell RNA-Seq analysis.Communications biology · 2024Article
- Building a learnable universal coordinate system for single-cell atlas with a joint-VAE model.Communications biology · 2024Article
- Large-scale foundation model on single-cell transcriptomics.Nature methods · 2024Article
- Hierarchical and automated cell-type annotation and inference of cancer cell of origin with Census.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
26 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accumulation of massive single-cell omics data provides growing resources for building biomolecular atlases of all cells of human organs or the whole body. The true assembly of a cell atlas should be cell-centric rather than file-centric. We developed a unified informatics framework for seamless cell-centric data assembly and built the human Ensemble Cell Atlas (hECA) from scattered data. hECA v1.0 assembled 1,093,299 labeled human cells from 116 published datasets, covering 38 organs and 11 systems. We invented three new methods of atlas applications based on the cell-centric assembly: "
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.