ArticleCell reports methods2023
BOMA, a machine-learning framework for comparative gene expression analysis across brains and organoids.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Using Brain Organoids to Explore Human Neurobiology.Cellular and molecular neurobiology · 2026Review
- Next-Generation Strategies for Neural Repair and Regeneration: Neural Organoid Transplantation in the CNS.Cell proliferation · 2026Review
- Cell type-agnostic transcriptomic signatures enable uniform comparisons of neural maturation.PLoS biology · 2026Article
- Inflammasomes meet organoids and artificial intelligence: unraveling the complexity of gynecological inflammation.Frontiers in immunology · 2026Review
- Deliod a lightweight detection model for intestinal organoids based on deep learning.Scientific reports · 2025Article
- Application of human cardiac organoids in cardiovascular disease research.Frontiers in cell and developmental biology · 2025Review
- Protocol for comparative gene expression data analysis between brains and organoids using a cloud-based web app.STAR protocols · 2024Article
- Harnessing the power of artificial intelligence for human living organoid research.Bioactive materials · 2024Review
- Consequences of trisomy 21 for brain development in Down syndrome.Nature reviews. Neuroscience · 2024Review
- Cross-site reproducibility of human cortical organoids reveals consistent cell type composition and architecture.Stem cell reports · 2024Article
- From wings to whiskers to stem cells: why every model matters in fragile X syndrome research.Journal of neurodevelopmental disorders · 2024Review
- SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.Cell genomics · 2024Article
- Rigor and reproducibility in human brain organoid research: Where we are and where we need to go.Stem cell reports · 2024Review
- AI-organoid integrated systems for biomedical studies and applications.Bioengineering & translational medicine · 2024Review
- Organoid intelligence: Integration of organoid technology and artificial intelligence in the new era of in vitro models.Medicine in novel technology and devices · 2024Article
- AI-enabled organoids: Construction, analysis, and application.Bioactive materials · 2024Review
- Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
13 authors.
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Abstract
Our machine-learning framework, brain and organoid manifold alignment (BOMA), first performs a global alignment of developmental gene expression data between brains and organoids. It then applies manifold learning to locally refine the alignment, revealing conserved and specific developmental trajectories across brains and organoids. Using BOMA, we found that human cortical organoids better align with certain brain cortical regions than with other non-cortical regions, implying organoid-preserved developmental gene expression programs specific to brain regions. Additionally, our alignment of non-human primate and human brains reveals highly conserved gene expression around birth. Also, we integrated and analyzed developmental single-cell RNA sequencing (scRNA-seq) data of human brains and organoids, showing conserved and specific cell trajectories and clusters. Further identification of expressed genes of such clusters and enrichment analyses reveal brain- or organoid-specific developmental functions and pathways. Finally, we experimentally validated important specific expressed genes through the use of immunofluorescence. BOMA is open-source available as a web tool for community use.
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