ArticleCell stem cell2016
De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.
Article in Cell stem cell, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 310 papers.
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Who cites it
310 citing papers in PubMed.
- Tissue-Level Transcriptomic Entropy Reveals Organ-Specific Aging Patterns and Predicts Cancer Progression.Aging cell · 2026Article
- Interspecific diversity in the neuronal composition of the mammalian cortex arises from heterochrony in neurogenesis.The EMBO journal · 2026Article
- Organism-scale annotation with Pan-human Azimuth.bioRxiv : the preprint server for biology · 2026Article
- A 3D spatial proteomic map of the human pancreatic islet microenvironment.Research square · 2026Article
- mmContext: an open framework for multimodal contrastive learning of omics and text data.Bioinformatics (Oxford, England) · 2026Article
- Deep single-cell decoding of human pancreatic islets reveals T2D β-cell gene expression defects.The EMBO journal · 2026Article
- Cancer-associated fibroblast subtype signature gene predicts survival and immunotherapy response in sarcoma.PloS one · 2026Article
- Regulatory element modules as universal features for single-cell chromatin analysis.bioRxiv : the preprint server for biology · 2025Article
- Article
- Fast Optimization of Robust Transcriptomics Embeddings using Probabilistic Inference Autoencoder Networks for multi-Omics.bioRxiv : the preprint server for biology · 2025Article
- PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories.Nature methods · 2025Article
- Evaluating cell-specific gene expression using single-cell and single-nuclei RNA-sequencing data from human pancreatic islets of the same donors.Scientific reports · 2025Article
- Characterization of quiescent subpopulations and proliferative compartments in glioblastoma.bioRxiv : the preprint server for biology · 2025Article
- Resolving early embryonic metabolism in Drosophila through single-embryo metabolomics and transcriptomics.Nature metabolism · 2025Article
- Spatially resolved endothelial signaling via nampt-itga5 drives immune evasion in stem-like gastric cancer.Cancer immunology, immunotherapy : CII · 2025Article
- ScAGCN: Graph Convolutional Network with Adaptive Aggregation Mechanism for scRNA-seq Data Dimensionality Reduction.Interdisciplinary sciences, computational life sciences · 2025Article
- Single-cell multi-omics and machine learning for dissecting stemness in cancer.Briefings in bioinformatics · 2025Review
- The intrinsic dimension of gene expression during cell differentiation.Nucleic acids research · 2025Article
- Live-cell omics with Raman spectroscopy.Microscopy (Oxford, England) · 2025Review
- Uncovering candidate Nanog-Helper genes in early mouse embryo differentiation using differential entropy and network inference.Scientific reports · 2025Article
250 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
Adult mitotic tissues like the intestine, skin, and blood undergo constant turnover throughout the life of an organism. Knowing the identity of the stem cell is crucial to understanding tissue homeostasis and its aberrations upon disease. Here we present a computational method for the derivation of a lineage tree from single-cell transcriptome data. By exploiting the tree topology and the transcriptome composition, we establish StemID, an algorithm for identifying stem cells among all detectable cell types within a population. We demonstrate that StemID recovers two known adult stem cell populations, Lgr5+ cells in the small intestine and hematopoietic stem cells in the bone marrow. We apply StemID to predict candidate multipotent cell populations in the human pancreas, a tissue with largely uncharacterized turnover dynamics. We hope that StemID will accelerate the search for novel stem cells by providing concrete markers for biological follow-up and validation.
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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.