ArticleProceedings of the National Academy of Sciences of the United States of America2014
Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers.
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Who cites it
146 citing papers in PubMed.
- Recurrent neural chemical reaction networks trained to switch dynamical behaviours through learned bifurcations.Journal of the Royal Society, Interface · 2026Article
- Dynamic Landscape Analysis of cell fate decisions provides predictive models of neural development from single-cell data.PLoS biology · 2026Article
- Mosaic: Single-Cell Atlas of Stress.Cells · 2026Review
- NF-κB epigenetic attractor landscape drives breast cancer heterogeneity.NPJ systems biology and applications · 2025Article
- Clinical application of single-cell RNA sequencing in disease and therapy.Clinical and translational medicine · 2025Review
- Generative AI Models in Time-Varying Biomedical Data: Scoping Review.Journal of medical Internet research · 2025Article
- Dynamics of computational waveform: A study of bifurcation, chaos, and sensitivity analysis.PloS one · 2025Article
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- Chromatin accessibility is associated with therapeutic response in prostate cancer.Oncology letters · 2024Article
- scGRN-Entropy: Inferring cell differentiation trajectories using single-cell data and gene regulation network-based transfer entropy.PLoS computational biology · 2024Article
- Article
- scCURE identifies cell types responding to immunotherapy and enables outcome prediction.Cell reports methods · 2023Article
- Identifying a developmental transition in honey bees using gene expression data.PLoS computational biology · 2023Article
- Bifurcation instructed design of multistate machines.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Systematic analysis and optimization of early warning signals for critical transitions using distribution data.iScience · 2023Article
- A dynamical systems treatment of transcriptomic trajectories in hematopoiesis.Development (Cambridge, England) · 2023Article
- Multi-Objective Genetic Algorithm for Cluster Analysis of Single-Cell Transcriptomes.Journal of personalized medicine · 2023Article
- Single-cell Senseless protein analysis reveals metastable states during the transition to a sensory organ fate.iScience · 2022Article
- Dynamical landscapes of cell fate decisions.Interface focus · 2022Review
- Comparison of cell state models derived from single-cell RNA sequencing data: graph versus multi-dimensional space.Mathematical biosciences and engineering : MBE · 2022Article
86 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
We present single-cell clustering using bifurcation analysis (SCUBA), a novel computational method for extracting lineage relationships from single-cell gene expression data and modeling the dynamic changes associated with cell differentiation. SCUBA draws techniques from nonlinear dynamics and stochastic differential equation theories, providing a systematic framework for modeling complex processes involving multilineage specifications. By applying SCUBA to analyze two complementary, publicly available datasets we successfully reconstructed the cellular hierarchy during early development of mouse embryos, modeled the dynamic changes in gene expression patterns, and predicted the effects of perturbing key transcriptional regulators on inducing lineage biases. The results were robust with respect to experimental platform differences between RT-PCR and RNA sequencing. We selectively tested our predictions in Nanog mutants and found good agreement between SCUBA predictions and the experimental data. We further extended the utility of SCUBA by developing a method to reconstruct missing temporal-order information from a typical single-cell dataset. Analysis of a hematopoietic dataset suggests that our method is effective for reconstructing gene expression dynamics during human B-cell development. In summary, SCUBA provides a useful single-cell data analysis tool that is well-suited for the investigation of developmental processes.
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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.