ArticleBMC bioinformatics2017
Enhanced construction of gene regulatory networks using hub gene information.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
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Who cites it
75 citing papers in PubMed.
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- AttBiomarker: unveiling preeclampsia biomarkers and molecular pathways through two-stage gene selection techniques and attention-based CNN with gene regulatory network analysis.Briefings in bioinformatics · 2025Article
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- Transcriptomic analysis of human cartilage identified potential therapeutic targets for hip osteoarthritis.Human molecular genetics · 2025Article
- Patient-centered brain transcriptomic and multimodal imaging determinants of clinical progression, physical activity, and treatment needs in Parkinson's disease.NPJ Parkinson's disease · 2025Article
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- Comparative temporal transcriptome analyses of SARS-CoV-2 delta and omicron variants ex-vivo infection in cat lung explant culture.Frontiers in cellular and infection microbiology · 2025Article
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- Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria.Frontiers in genetics · 2025Article
- High-dimensional co-expression network analysis reveals persistent TRH gene expression throughout axolotl telencephalon regeneration.Frontiers in bioinformatics · 2025Article
- Network-based multi-class classifier to identify optimized gene networks for acute leukemia cell line classification.PloS one · 2025Article
- Identification of Novel Modifier Genes Associated With Pain in Cystic Fibrosis: An In Silico Gene Discovery.Human mutation · 2025Article
- HORNET: tools to find genes with causal evidence and their regulatory networks using eQTLs.Bioinformatics advances · 2025Article
- Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives.Current medicinal chemistry · 2025Review
- Nei 6 You 7075, a hybrid rice cultivar, exhibits enhanced disease resistance and drought tolerance traits.BMC plant biology · 2024Article
15 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
backgroundGene regulatory networks reveal how genes work together to carry out their biological functions. Reconstructions of gene networks from gene expression data greatly facilitate our understanding of underlying biological mechanisms and provide new opportunities for biomarker and drug discoveries. In gene networks, a gene that has many interactions with other genes is called a hub gene, which usually plays an essential role in gene regulation and biological processes. In this study, we developed a method for reconstructing gene networks using a partial correlation-based approach that incorporates prior information about hub genes. Through simulation studies and two real-data examples, we compare the performance in estimating the network structures between the existing methods and the proposed method.
resultsIn simulation studies, we show that the proposed strategy reduces errors in estimating network structures compared to the existing methods. When applied to Escherichia coli, the regulation network constructed by our proposed ESPACE method is more consistent with current biological knowledge than the SPACE method. Furthermore, application of the proposed method in lung cancer has identified hub genes whose mRNA expression predicts cancer progress and patient response to treatment.
conclusionsWe have demonstrated that incorporating hub gene information in estimating network structures can improve the performance of the existing methods.
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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.