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CySBGN: a Cytoscape plug-in to integrate SBGN maps.
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Modeling signaling networks with different formalisms: a preview.
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Construction of cell type-specific logic models of signaling networks using CellNOpt.
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Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.
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DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data.
Pacini et al. Bioinformatics, 2012
CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.
Terfve et al. Bmc Syst Biol, 2012
Transcriptional data: a new gateway to drug repositioning?
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MacNamara et al. Phys Biol, 2012
Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.
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Integrating literature-constrained and data-driven inference of signalling networks.
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Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks.
Kirouac et al. Bmc Syst Biol, 2012
Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.
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Mapping the human phosphatome on growth pathways.
Sacco et al. Mol Syst Biol, 2012
Modeling signaling networks using high-throughput phospho-proteomics.
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Crowdsourcing network inference: the DREAM predictive signaling network challenge.
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Comparing signaling networks between normal and transformed hepatocytes using discrete logical models.
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Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.
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Setting the standards for signal transduction research.
Saez-Rodriguez et al. Sci Signal, 2011
Networks inferred from biochemical data reveal profound differences in toll-like receptor and inflammatory signaling between normal and transformed hepatocytes.
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Towards a rigorous assessment of systems biology models: the DREAM3 challenges.
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