ArticleBioinformatics (Oxford, England)2012
Bayesian inference of signaling network topology in a cancer cell line.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Statistical genomics in rare cancer.Seminars in cancer biology · 2020Pooled it
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- Causal models and prediction in cell line perturbation experiments.BMC bioinformatics · 2025Article
- Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.Clinical Medicine Insights. Oncology · 2025Review
- 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
- Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024Review
- Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.Molecules and cells · 2021Review
- Inferring signaling pathways with probabilistic programming.Bioinformatics (Oxford, England) · 2020Article
- Perturbation biology links temporal protein changes to drug responses in a melanoma cell line.PLoS computational biology · 2020Article
- Network inference in systems biology: recent developments, challenges, and applications.Current opinion in biotechnology · 2020Review
- Article
- D3GRN: a data driven dynamic network construction method to infer gene regulatory networks.BMC genomics · 2019Article
- Inferring Regulatory Programs Governing Region Specificity of Neuroepithelial Stem Cells during Early Hindbrain and Spinal Cord Development.Cell systems · 2019Article
- Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data.Essays in biochemistry · 2018Review
- Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data.Cell reports · 2018Article
- Encoding Growth Factor Identity in the Temporal Dynamics of FOXO3 under the Combinatorial Control of ERK and AKT Kinases.Cell systems · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
motivationProtein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure.
resultsIn this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers. AVAILABILITY: http://mukherjeelab.nki.nl/DBN (code and data).
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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.