ArticleCell systems2017
Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 46 citations in OpenAlex.
- Literature-derived, context-aware gene regulatory networks improve biological predictions and mathematical modeling.Bioinformatics (Oxford, England) · 2026Article
- Large-scale mapping of environmental-genetic interactions illustrates the dynamic nature of cell-cycle and DNA repair regulation.Molecular cell · 2026Article
- Systems-level reconstruction of kinase phosphosignaling networks regulating endothelial barrier integrity using temporal data.NPJ systems biology and applications · 2024Article
- Systems-level reconstruction of kinase phosphosignaling networks regulating endothelial barrier integrity using temporal data.bioRxiv : the preprint server for biology · 2024Article
- Gene regulatory networks in disease and ageing.Nature reviews. Nephrology · 2024Review
- Network inference from perturbation time course data.NPJ systems biology and applications · 2022Article
- Bone Marrow Endothelial Cells Increase Prostate Cancer Cell Apoptosis in 3D Triculture Model of Reactive Stroma.Biology · 2022Article
- Establishing Institutional Scores With the Rigor and Transparency Index: Large-scale Analysis of Scientific Reporting Quality.Journal of medical Internet research · 2022Article
- Causal reasoning over knowledge graphs leveraging drug-perturbed and disease-specific transcriptomic signatures for drug discovery.PLoS computational biology · 2022Article
- Causal interactions from proteomic profiles: Molecular data meet pathway knowledge.Patterns (New York, N.Y.) · 2021Article
- Article
- Inferring signaling pathways with probabilistic programming.Bioinformatics (Oxford, England) · 2020Article
- Explicit representation of protein activity states significantly improves causal discovery of protein phosphorylation networks.BMC bioinformatics · 2020Article
- Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies.Molecular systems biology · 2020Article
- Mechanistic Model of Signaling Dynamics Across an Epithelial Mesenchymal Transition.Frontiers in physiology · 2020Article
- Causal Learning via Manifold Regularization.Journal of machine learning research : JMLR · 2019Article
- Capturing context-specific regulation in molecular interaction networks.BMC bioinformatics · 2018Article
- Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data.Essays in biochemistry · 2018Review
- Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data.PLoS computational biology · 2018Article
- Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data.Cell reports · 2018Article
Corrections and comments
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Authors and funding
16 authors at 7 institutions in 3 countries.
Funding
Abstract
Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.
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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 OpenQuestion graph.