ArticlePloS one2015
Predicting Variabilities in Cardiac Gene Expression with a Boolean Network Incorporating Uncertainty.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 27 citations in OpenAlex.
- Molecular insights into heart field-specific cardiomyocyte differentiation - A computational study.PloS one · 2026Article
- Correlations reveal the hierarchical organization of biological networks with latent variables.Communications biology · 2024Article
- The nonlinearity of regulation in biological networks.NPJ systems biology and applications · 2023Article
- Boolean network sketches: a unifying framework for logical model inference.Bioinformatics (Oxford, England) · 2023Article
- Leveraging quantum computing for dynamic analyses of logical networks in systems biology.Patterns (New York, N.Y.) · 2023Article
- Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses.Frontiers in bioinformatics · 2023Article
- Discrete Logic Modeling of Cell Signaling Pathways.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Quantification of uncertainty in a new network model of pulmonary arterial adventitial fibroblast pro-fibrotic signalling.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
- Concepts in Boolean network modeling: What do they all mean?Computational and structural biotechnology journal · 2020Review
- The Wnt inhibitor Dkk1 is required for maintaining the normal cardiac differentiation program in Xenopus laevis.Developmental biology · 2019Article
- Representing dynamic biological networks with multi-scale probabilistic models.Communications biology · 2019Article
- Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.Frontiers in physiology · 2018Article
- A Boolean network of the crosstalk between IGF and Wnt signaling in aging satellite cells.PloS one · 2018Article
- CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.BMC bioinformatics · 2016Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene interactions in cells can be represented by gene regulatory networks. A Boolean network models gene interactions according to rules where gene expression is represented by binary values (on / off or {1, 0}). In reality, however, the gene's state can have multiple values due to biological properties. Furthermore, the noisy nature of the experimental design results in uncertainty about a state of the gene. Here we present a new Boolean network paradigm to allow intermediate values on the interval [0, 1]. As in the Boolean network, fixed points or attractors of such a model correspond to biological phenotypes or states. We use our new extension of the Boolean network paradigm to model gene expression in first and second heart field lineages which are cardiac progenitor cell populations involved in early vertebrate heart development. By this we are able to predict additional biological phenotypes that the Boolean model alone is not able to identify without utilizing additional biological knowledge. The additional phenotypes predicted by the model were confirmed by published biological experiments. Furthermore, the new method predicts gene expression propensities for modelled but yet to be analyzed genes.
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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.