ReviewJournal of cell science2013
Models of signalling networks - what cell biologists can gain from them and give to them.
Review in Journal of cell science, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed.
- Biomarkers and immunomodulatory effect of erythropoietin in postoperative ileus.BMC research notes · 2026Article
- Article
- Generating synthetic signaling networks for in silico modeling studies.Journal of theoretical biology · 2024Article
- Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3DBiophysics reviews · 2024Review
- Phenotypic consequences of logarithmic signaling in MAPK stress response.bioRxiv : the preprint server for biology · 2023Article
- Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors.Frontiers in pharmacology · 2023Article
- Modelling human liver fibrosis in the context of non-alcoholic steatohepatitis using a microphysiological system.Communications biology · 2021Article
- Dynamic modelling of the PI3K/MTOR signalling network uncovers biphasic dependence of mTORC1 activity on the mTORC2 subunit SIN1.PLoS computational biology · 2021Article
- Unsupervised logic-based mechanism inference for network-driven biological processes.PLoS computational biology · 2021Article
- Modeling the complete kinetics of coxsackievirus B3 reveals human determinants of host-cell feedback.Cell systems · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- Article
- Article
- Combining Mathematical Models With Experimentation to Drive Novel Mechanistic Insights Into Macrophage Function.Frontiers in immunology · 2019Article
- Mechanistic Models of Cellular Signaling, Cytokine Crosstalk, and Cell-Cell Communication in Immunology.Frontiers in immunology · 2019Article
- High-throughput combinatorial screening reveals interactions between signaling molecules that regulate adult neural stem cell fate.Biotechnology and bioengineering · 2019Article
- Article
- PyDREAM: high-dimensional parameter inference for biological models in python.Bioinformatics (Oxford, England) · 2018Article
- VEGFR1 promotes cell migration and proliferation through PLCγ and PI3K pathways.NPJ systems biology and applications · 2018Article
- System identification of signaling dependent gene expression with different time-scale data.PLoS computational biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Computational models of cell signalling are perceived by many biologists to be prohibitively complicated. Why do math when you can simply do another experiment? Here, we explain how conceptual models, which have been formulated mathematically, have provided insights that directly advance experimental cell biology. In the past several years, models have influenced the way we talk about signalling networks, how we monitor them, and what we conclude when we perturb them. These insights required wet-lab experiments but would not have arisen without explicit computational modelling and quantitative analysis. Today, the best modellers are cross-trained investigators in experimental biology who work closely with collaborators but also undertake experimental work in their own laboratories. Biologists would benefit by becoming conversant in core principles of modelling in order to identify when a computational model could be a useful complement to their experiments. Although the mathematical foundations of a model are useful to appreciate its strengths and weaknesses, they are not required to test or generate a worthwhile biological hypothesis computationally.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.