ArticleInternational journal of molecular medicine2015
Identification of hub subnetwork based on topological features of genes in breast cancer.
Article in International journal of molecular medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 41 citations in OpenAlex.
- Network pharmacology identifies repurposable drugs targeting host pathways across the oral-gut-lung axis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Repurposing Nirmatrelvir for Hepatocellular Carcinoma: Network Pharmacology and Molecular Dynamics Simulations Identify HDAC3 as a Key Molecular Target.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems biology approach.BMC plant biology · 2025Article
- Constructing a disease-specific ceRNA coregulatory network for keratoconus diagnosis and landscape of the immune environment.International ophthalmology · 2025Article
- Article
- RegEnrich gene regulator enrichment analysis reveals a key role of the ETS transcription factor family in interferon signaling.Communications biology · 2022Article
- Meta-analysis of transcriptomics data identifies potential biomarkers and their associated regulatory networks in gallbladder cancer.Gastroenterology and hepatology from bed to bench · 2022Review
- Co-overexpression ofFrontiers in plant science · 2022Article
- PAICS is related to glioma grade and can promote glioma growth and migration.Journal of cellular and molecular medicine · 2021Article
- Identification of Differentially Expressed Genes in Cervical Cancer Patients by Comparative Transcriptome Analysis.BioMed research international · 2021Article
- An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer.Scientific reports · 2020Article
- A Novel lncRNA, AK130181, Contributes to HIV-1 Latency by Regulating Viral Promoter-Driven Gene Expression in Primary CD4Molecular therapy. Nucleic acids · 2020Article
- Article
- Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis.BioMed research international · 2020Article
- Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray.Biomolecules · 2019Article
- Analysis of protein-protein interaction network based on transcriptome profiling of ovine granulosa cells identifies candidate genes in cyclic recruitment of ovarian follicles.Journal of animal science and technology · 2018Article
- Genome-scale analysis identifies SERPINE1 and SPARC as diagnostic and prognostic biomarkers in gastric cancer.OncoTargets and therapy · 2018Article
- Unveiling Active Constituents and Potential Targets Related to the Hematinic Effect of SteamedFrontiers in pharmacology · 2018Article
- A novel method to identify differential pathways in uterine leiomyomata based on network strategy.Oncology letters · 2017Article
- Screening of the prognostic targets for breast cancer based co-expression modules analysis.Molecular medicine reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer.
Indexed as
Identifiers
What OpenQuestion holds
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.