ArticleGenome biology2024
Mapping lineage-traced cells across time points with moslin.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- The development of single-cell lineage tracing technology and its application in immunotherapy.Molecular therapy. Advances · 2026Review
- Charting single-cell lineages with synthetic and natural barcodes.Nature reviews. Genetics · 2026Review
- MiTo: tracing the phenotypic evolution of somatic cell lineages via mitochondrial single-cell multi-omics.Nature communications · 2026Article
- Cell trajectory inference based on schrödinger problem and a mechanistic model of stochastic gene expression.NPJ systems biology and applications · 2026Article
- Advancing single-cell omics and cell-based therapeutics with quantum computing.Nature reviews. Molecular cell biology · 2026Review
- Trajectory inference for a branching SDE model of cell differentiation via lineage tracing.Journal of mathematical biology · 2026Article
- Single-cell mitochondrial lineage tracing: Opportunities and challenges.Quantitative biology (Beijing, China) · 2026Review
- Generative models of cell dynamics: from Neural ODEs to flow matching.Communications biology · 2026Review
- Deciphering cell-fate trajectories using spatiotemporal single-cell transcriptomic data.NPJ systems biology and applications · 2025Review
- SCOUT: Ornstein-Uhlenbeck modelling of gene expression evolution on single-cell lineage trees.bioRxiv : the preprint server for biology · 2025Article
- Decoding cell fate: integrated experimental and computational analysis at the single-cell level.Bioinformatics (Oxford, England) · 2025Review
- Quantifying Landscape and Flux from Single-Cell Omics: Unraveling the Physical Mechanisms of Cell Function.JACS Au · 2025Review
- Unlocking Cellular Memory and Gene Regulatory Networks: Pioneering the Future of Therapeutic Innovations.Cells · 2025Article
- Computational modeling of single-cell dynamics data.Briefings in bioinformatics · 2025Review
- The lives of cells, recorded.Nature reviews. Genetics · 2025Review
- Interpreting single-cell and spatial omics data using deep neural network training dynamics.Nature computational science · 2024Article
- Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system.Nature neuroscience · 2024Review
- Mapping lineage-traced cells across time points with moslin.Genome biology · 2024Article
- CellRank 2: unified fate mapping in multiview single-cell data.Nature methods · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making. Recent computational approaches combine both modalities into cellular trajectories; however, they cannot make use of all available lineage information in destructive time-series experiments. Here, we present moslin, a Gromov-Wasserstein-based model to couple cellular profiles across time points based on lineage and gene expression information. We validate our approach in simulations and demonstrate on Caenorhabditis elegans embryonic development how moslin predicts fate probabilities and putative decision driver genes. Finally, we use moslin to delineate lineage relationships among transiently activated fibroblast states during zebrafish heart regeneration.
Indexed as
Identifiers
What OpenQuestion holds
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.