ArticleBioinformatics (Oxford, England)2013
Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed, 93 citations in OpenAlex.
- ScanNet: Single-cell annotation informed by transcriptional regulation Network via iterative heterogeneous graph learning.PLoS computational biology · 2026Article
- GPU-accelerated modeling of biological regulatory networks.Scientific reports · 2026Article
- KGBN: Augmenting and optimizing logical gene regulatory networks using knowledge graphs.bioRxiv : the preprint server for biology · 2026Article
- LM-Merger: a workflow for merging logical models with an application to gene regulatory network models.BMC bioinformatics · 2025Article
- A neural network-based model framework for cell-fate decisions and development.Communications biology · 2024Article
- Statistical control of structural networks with limited interventions to minimize cellular phenotypic diversity represented by point attractors.Scientific reports · 2023Article
- A novel Boolean network inference strategy to model early hematopoiesis aging.Computational and structural biotechnology journal · 2023Article
- Unveiling the complexity of transcription factor networks in hematopoietic stem cells: implications for cell therapy and hematological malignancies.Frontiers in oncology · 2023Review
- Single Cell Transcriptomics to Understand HSC Heterogeneity and Its Evolution upon Aging.Cells · 2022Review
- Boolean modelling in plant biology.Quantitative plant biology · 2022Review
- Data-driven modeling predicts gene regulatory network dynamics during the differentiation of multipotential hematopoietic progenitors.PLoS computational biology · 2022Article
- Statistical mechanics meets single-cell biology.Nature reviews. Genetics · 2021Review
- Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks.Science advances · 2021Article
- Single-cell RNA-seq reveals a concomitant delay in differentiation and cell cycle of aged hematopoietic stem cells.BMC biology · 2021Article
- An Early Stage Researcher's Primer on Systems Medicine Terminology.Network and systems medicine · 2021Review
- Dynamic Modeling of Transcriptional Gene Regulatory Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Inhibition of 3-phosphoinositide-dependent protein kinase 1 (PDK1) can revert cellular senescence in human dermal fibroblasts.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Classification-Based Inference of Dynamical Models of Gene Regulatory Networks.G3 (Bethesda, Md.) · 2019Article
- Executable pathway analysis using ensemble discrete-state modeling for large-scale data.PLoS computational biology · 2019Article
- The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
motivationCombinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes.
resultsDespite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.