ArticleMolecular systems biology2012
A framework for mapping, visualisation and automatic model creation of signal-transduction networks.
Article in Molecular systems biology, 2012. 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.
- Rules railroad: Syntax-inspired diagrams for visualizing and understanding rule-based model specifications.PLoS computational biology · 2026Article
- Visualizing mechanistic models by integrating site-specific molecular details into reaction networks.Frontiers in molecular biosciences · 2025Article
- bnglViz: online visualization of rule-based models.Bioinformatics (Oxford, England) · 2024Article
- kboolnet: a toolkit for the verification, validation, and visualization of reaction-contingency (rxncon) models.BMC bioinformatics · 2023Article
- A detailed molecular network map and model of the NLRP3 inflammasome.Frontiers in immunology · 2023Review
- Modelling of glucose repression signalling in yeast Saccharomyces cerevisiae.FEMS yeast research · 2022Review
- From Petri Plates to Petri Nets, a revolution in yeast biology.FEMS yeast research · 2022Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- Article
- A scalable method for parameter-free simulation and validation of mechanistic cellular signal transduction network models.NPJ systems biology and applications · 2020Article
- A comprehensive, mechanistically detailed, and executable model of the cell division cycle in Saccharomyces cerevisiae.Nature communications · 2019Article
- Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response.PLoS computational biology · 2018Article
- From word models to executable models of signaling networks using automated assembly.Molecular systems biology · 2017Article
- Automated visualization of rule-based models.PLoS computational biology · 2017Article
- Systems Level Analysis of the Yeast Osmo-Stat.Scientific reports · 2016Article
- Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.PloS one · 2016Article
- Stochastic simulation of Boolean rxncon models: towards quantitative analysis of large signaling networks.BMC systems biology · 2015Article
- The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms.BMC systems biology · 2015Article
- Modeling for (physical) biologists: an introduction to the rule-based approach.Physical biology · 2015Review
- Network reconstruction and validation of the Snf1/AMPK pathway in baker's yeast based on a comprehensive literature review.NPJ systems biology and applications · 2015Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Intracellular signalling systems are highly complex. This complexity makes handling, analysis and visualisation of available knowledge a major challenge in current signalling research. Here, we present a novel framework for mapping signal-transduction networks that avoids the combinatorial explosion by breaking down the network in reaction and contingency information. It provides two new visualisation methods and automatic export to mathematical models. We use this framework to compile the presently most comprehensive map of the yeast MAP kinase network. Our method improves previous strategies by combining (I) more concise mapping adapted to empirical data, (II) individual referencing for each piece of information, (III) visualisation without simplifications or added uncertainty, (IV) automatic visualisation in multiple formats, (V) automatic export to mathematical models and (VI) compatibility with established formats. The framework is supported by an open source software tool that facilitates integration of the three levels of network analysis: definition, visualisation and mathematical modelling. The framework is species independent and we expect that it will have wider impact in signalling research on any system.
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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.