ArticleScience advances2022
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 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
53 citing papers in PubMed, 83 citations in OpenAlex.
- Mechanistic machine learning for prediction of prime editing outcomes.Nature biotechnology · 2026Article
- Mathematical and Computational Models of Biochemical Reactions and Cell Signaling-From Ordinary Differential Equations to Machine Learning.International journal of molecular sciences · 2026Review
- Leveraging Lineage Barcodes as Natural Augmentations for Contrastive Learning of Cell Fate in scRNA-seq Data.bioRxiv : the preprint server for biology · 2026Article
- Inferring stochastic dynamics by biophysical Neural ODE using single-cell transcriptomics.Nature communications · 2026Article
- Comparison between a conventional tool and deep learning models for RNA velocity analysis of scRNA-Seq data.Molecular genetics and genomics : MGG · 2026Article
- CRAK-Velo: chromatin accessibility kinetics integration improves RNA velocity estimation.Genome biology · 2026Article
- Benchmarking RNA velocity methods across 17 independent studies.Cell reports methods · 2026Article
- Interpretable learning of temporal cellular dynamics from single-cell data.Cell reports methods · 2026Article
- Neural network-assisted RNA velocity imputation for empowering transcript dynamics-based analyses.iScience · 2026Article
- iAODE for benchmarking and continuum modeling of single-cell chromatin accessibility.Communications biology · 2026Article
- Generative models of cell dynamics: from Neural ODEs to flow matching.Communications biology · 2026Review
- Mechanistic machine learning enables interpretable and generalizable prediction of prime editing outcomes.bioRxiv : the preprint server for biology · 2026Article
- APOE4-driven T cell dysregulation in Alzheimer's disease: single-cell genomics and Mendelian randomization reveal novel therapeutic targets.Journal of neuroinflammation · 2026Article
- Geometry-preserving vector field reconstruction of high-dimensional cell-state dynamics using ddHodge.Nature communications · 2025Article
- Fundamental errors in RNA velocity arising from the omission of cell growth.bioRxiv : the preprint server for biology · 2025Article
- Metabolic plasticity drives mechanisms of PARP inhibitor persistence in ovarian cancer.bioRxiv : the preprint server for biology · 2025Article
- Quantifying Landscape and Flux from Single-Cell Omics: Unraveling the Physical Mechanisms of Cell Function.JACS Au · 2025Review
- Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2025Article
- scMultiNODE: Integrative and Scalable Framework for Multi-Modal Temporal Single-Cell Data.bioRxiv : the preprint server for biology · 2025Article
- Discovering governing equations of biological systems through representation learning and sparse model discovery.NAR genomics and bioinformatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
Recent advances in single-cell sequencing technologies have provided unprecedented opportunities to measure the gene expression profile and RNA velocity of individual cells. However, modeling transcriptional dynamics is computationally challenging because of the high-dimensional, sparse nature of the single-cell gene expression measurements and the nonlinear regulatory relationships. Here, we present
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.