ArticleCancer informatics2014
Modeling the altered expression levels of genes on signaling pathways in tumors as causal bayesian networks.
Article in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Accelerating Bayesian inference of dependency between mixed-type biological traits.PLoS computational biology · 2023Article
- Synthetic data generation with probabilistic Bayesian Networks.Mathematical biosciences and engineering : MBE · 2021Article
- Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.G3 (Bethesda, Md.) · 2020Article
- Article
- New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.Journal of computational biology : a journal of computational molecular cell biology · 2017Article
- Modeling miRNA-mRNA interactions that cause phenotypic abnormality in breast cancer patients.PloS one · 2017Article
- Revealing Biological Pathways Implicated in Lung Cancer from TCGA Gene Expression Data Using Gene Set Enrichment Analysis.Cancer informatics · 2014Article
- Inferring Aberrant Signal Transduction Pathways in Ovarian Cancer from TCGA Data.Cancer informatics · 2014Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
This paper concerns a study indicating that the expression levels of genes in signaling pathways can be modeled using a causal Bayesian network (BN) that is altered in tumorous tissue. These results open up promising areas of future research that can help identify driver genes and therapeutic targets. So, it is most appropriate for the cancer informatics community. Our central hypothesis is that the expression levels of genes that code for proteins on a signal transduction network (STP) are causally related and that this causal structure is altered when the STP is involved in cancer. To test this hypothesis, we analyzed 5 STPs associated with breast cancer, 7 STPs associated with other cancers, and 10 randomly chosen pathways, using a breast cancer gene expression level dataset containing 529 cases and 61 controls. We identified all the genes related to each of the 22 pathways and developed separate gene expression datasets for each pathway. We obtained significant results indicating that the causal structure of the expression levels of genes coding for proteins on STPs, which are believed to be implicated in both breast cancer and in all cancers, is more altered in the cases relative to the controls than the causal structure of the randomly chosen pathways.
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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.