ArticleJournal of bone metabolism2018
Causal Inference Network of Genes Related with Bone Metastasis of Breast Cancer and Osteoblasts Using Causal Bayesian Networks.
Article in Journal of bone metabolism, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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15 citing papers in PubMed, 21 citations in OpenAlex.
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- Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art.Genetic epidemiology · 2026Review
- Prediction Model for Low Bone Mineral Density in Cancer Survivors and Age-Matched Controls Using a Causal Bayesian Network: A Nationwide Population-Based Study in Korea.Clinical Medicine Insights. Oncology · 2026Article
- Identification of Bone Metastasis-Related Gene Networks in Lung Cancer: Implications for Bone Metabolism.Journal of bone metabolism · 2025Article
- Modelling Interventions to Combat Antibacterial Resistance in East Africa Using Causal Bayesian Networks.Research square · 2025Article
- Artificial Intelligence in Detection, Management, and Prognosis of Bone Metastasis: A Systematic Review.Cancers · 2024Review
- Association between genetically plasma proteins and osteonecrosis: a proteome-wide Mendelian randomization analysis.Frontiers in genetics · 2024Article
- Probabilistic graphical modelling using Bayesian networks for predicting clinical outcome after posterior decompression in patients with degenerative cervical myelopathy.Annals of medicine · 2023Article
- Redox-Cycling "Mitocans" as Effective New Developments in Anticancer Therapy.International journal of molecular sciences · 2023Article
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- Causal Bayesian gene networks associated with bone, brain and lung metastasis of breast cancer.Clinical & experimental metastasis · 2020Article
- The Tristetraprolin Family of RNA-Binding Proteins in Cancer: Progress and Future Prospects.Cancers · 2020Review
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- The Functional Role of Voltage-Gated Sodium Channel Nav1.5 in Metastatic Breast Cancer.Frontiers in pharmacology · 2020Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe causal networks among genes that are commonly expressed in osteoblasts and during bone metastasis (BM) of breast cancer (BC) are not well understood. Here, we developed a machine learning method to obtain a plausible causal network of genes that are commonly expressed during BM and in osteoblasts in BC.
methodsWe selected BC genes that are commonly expressed during BM and in osteoblasts from the Gene Expression Omnibus database. Bayesian Network Inference with Java Objects (Banjo) was used to obtain the Bayesian network. Genes registered as BC related genes were included as candidate genes in the implementation of Banjo. Next, we obtained the Bayesian structure and assessed the prediction rate for BM, conditional independence among nodes, and causality among nodes. Furthermore, we reported the maximum relative risks (RRs) of combined gene expression of the genes in the model.
resultsWe mechanistically identified 33 significantly related and plausibly involved genes in the development of BC BM. Further model evaluations showed that 16 genes were enough for a model to be statistically significant in terms of maximum likelihood of the causal Bayesian networks (CBNs) and for correct prediction of BM of BC. Maximum RRs of combined gene expression patterns showed that the expression levels of
conclusionsThe CBN structure can be used as a reasonable inference network for accurately predicting BM in BC.
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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.