ArticlePLoS computational biology2021
Quantifying cell transitions in C. elegans with data-fitted landscape models.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 26 citations in OpenAlex.
- Dynamic Landscape Analysis of cell fate decisions provides predictive models of neural development from single-cell data.PLoS biology · 2026Article
- From static definitions to dynamic landscapes: physiological states in yeast.Frontiers in microbiology · 2026Article
- Generative epigenetic landscapes map the topology and topography of cell fates.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Dynamical systems of fate and form in development.Seminars in cell & developmental biology · 2025Review
- From genes to patterns: five key dynamical systems concepts to decode developmental regulatory mechanisms.Development (Cambridge, England) · 2025Review
- Finding signatures of low-dimensional geometric landscapes in high-dimensional cell fate transitions.bioRxiv : the preprint server for biology · 2025Article
- Finding signatures of low-dimensional geometric landscapes in high-dimensional cell fate transitions.ArXiv · 2025Article
- Approximate Bayesian computation for inferring Waddington landscapes from single-cell data.Royal Society open science · 2024Article
- Combinatorial interpretation of BMP and WNT controls the decision between primitive streak and extraembryonic fates.Cell systems · 2024Article
- A dynamical systems treatment of transcriptomic trajectories in hematopoiesis.Development (Cambridge, England) · 2023Article
- Dynamical landscapes of cell fate decisions.Interface focus · 2022Review
- Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions.Cell systems · 2022Article
- Geometry of gene regulatory dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Increasing interest has emerged in new mathematical approaches that simplify the study of complex differentiation processes by formalizing Waddington's landscape metaphor. However, a rational method to build these landscape models remains an open problem. Here we study vulval development in C. elegans by developing a framework based on Catastrophe Theory (CT) and approximate Bayesian computation (ABC) to build data-fitted landscape models. We first identify the candidate qualitative landscapes, and then use CT to build the simplest model consistent with the data, which we quantitatively fit using ABC. The resulting model suggests that the underlying mechanism is a quantifiable two-step decision controlled by EGF and Notch-Delta signals, where a non-vulval/vulval decision is followed by a bistable transition to the two vulval states. This new model fits a broad set of data and makes several novel predictions.
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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.