ArticlePLoS computational biology2018
Transition state characteristics during cell differentiation.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- Review
- Auxin promotes robust founder cell specification during Arabidopsis lateral root initiation.Genetics · 2026Article
- Transitional cell states at the crossroads of development, disease, and repair-regeneration.Physiological reviews · 2026Review
- Molecular noise modulates transitions in the cell-fate differentiation landscape.NPJ systems biology and applications · 2026Article
- Branch-specific gene discovery in cell differentiation using multi-omics graph attention.PLoS computational biology · 2025Article
- Towards a mathematical framework for modelling cell fate dynamics.Journal of mathematical biology · 2025Article
- Learning stochastic processes with intrinsic noise from cross-sectional biological data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.Development (Cambridge, England) · 2025Review
- Article
- A statistical approach for systematic identification of transition cells from scRNA-seq data.Cell reports methods · 2024Article
- Approximate Bayesian computation for inferring Waddington landscapes from single-cell data.Royal Society open science · 2024Article
- The energetics of cellular life transitions.Life metabolism · 2024Article
- Reversing pathological cell states: the road less travelled can extend the therapeutic horizon.Trends in cell biology · 2023Review
- Characterization of cell-fate decision landscapes by estimating transcription factor dynamics.Cell reports methods · 2023Article
- BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity.Nature communications · 2023Article
- From 'Omics to Multi-omics Technologies: the Discovery of Novel Causal Mediators.Current atherosclerosis reports · 2023Review
- Early enforcement of cell identity by a functional component of the terminally differentiated state.PLoS biology · 2022Article
- Article
- Control of cell state transitions.Nature · 2022Article
- Dynamical landscapes of cell fate decisions.Interface focus · 2022Review
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Authors and funding
3 authors.
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Abstract
Models describing the process of stem-cell differentiation are plentiful, and may offer insights into the underlying mechanisms and experimentally observed behaviour. Waddington's epigenetic landscape has been providing a conceptual framework for differentiation processes since its inception. It also allows, however, for detailed mathematical and quantitative analyses, as the landscape can, at least in principle, be related to mathematical models of dynamical systems. Here we focus on a set of dynamical systems features that are intimately linked to cell differentiation, by considering exemplar dynamical models that capture important aspects of stem cell differentiation dynamics. These models allow us to map the paths that cells take through gene expression space as they move from one fate to another, e.g. from a stem-cell to a more specialized cell type. Our analysis highlights the role of the transition state (TS) that separates distinct cell fates, and how the nature of the TS changes as the underlying landscape changes-change that can be induced by e.g. cellular signaling. We demonstrate that models for stem cell differentiation may be interpreted in terms of either a static or transitory landscape. For the static case the TS represents a particular transcriptional profile that all cells approach during differentiation. Alternatively, the TS may refer to the commonly observed period of heterogeneity as cells undergo stochastic transitions.
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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.