ReviewBioMed research international2016
Differential Regulatory Analysis Based on Coexpression Network in Cancer Research.
Review in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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
13 citing papers in PubMed.
- Peptide IRW upregulates ACE2 in spontaneously hypertensive rats via dopamine/D1R signaling pathway.Journal of advanced research · 2026Article
- A collaborative network analysis for the interpretation of transcriptomics data in Huntington's disease.Scientific reports · 2025Article
- Single-Sample Networks Reveal Intra-Cytoband Co-Expression Hotspots in Breast Cancer Subtypes.International journal of molecular sciences · 2024Article
- Signaling networks in inflammatory pathways and risk for suicidal behavior.Brain, behavior, & immunity - health · 2020Article
- Transcriptome differences in adipose stromal cells derived from pre- and postmenopausal women.Stem cell research & therapy · 2020Article
- Differential regulatory network-based quantification and prioritization of key genes underlying cancer drug resistance based on time-course RNA-seq data.PLoS computational biology · 2019Article
- Identification of hyper-rewired genomic stress non-oncogene addiction genes across 15 cancer types.NPJ systems biology and applications · 2019Article
- Differential Connectivity in Colorectal Cancer Gene Expression NetworkIranian biomedical journal · 2019Article
- Potential four‑miRNA signature associated with T stage and prognosis of patients with pancreatic ductal adenocarcinoma identified by co‑expression analysis.Molecular medicine reports · 2019Article
- BioNetStat: A Tool for Biological Networks Differential Analysis.Frontiers in genetics · 2019Article
- A powerful nonparametric method for detecting differentially co-expressed genes: distance correlation screening and edge-count test.BMC systems biology · 2018Article
- Article
- Exploring functions of long noncoding RNAs across multiple cancers through co-expression network.Scientific 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With rapid development of high-throughput techniques and accumulation of big transcriptomic data, plenty of computational methods and algorithms such as differential analysis and network analysis have been proposed to explore genome-wide gene expression characteristics. These efforts are aiming to transform underlying genomic information into valuable knowledges in biological and medical research fields. Recently, tremendous integrative research methods are dedicated to interpret the development and progress of neoplastic diseases, whereas differential regulatory analysis (DRA) based on gene coexpression network (GCN) increasingly plays a robust complement to regular differential expression analysis in revealing regulatory functions of cancer related genes such as evading growth suppressors and resisting cell death. Differential regulatory analysis based on GCN is prospective and shows its essential role in discovering the system properties of carcinogenesis features. Here we briefly review the paradigm of differential regulatory analysis based on GCN. We also focus on the applications of differential regulatory analysis based on GCN in cancer research and point out that DRA is necessary and extraordinary to reveal underlying molecular mechanism in large-scale carcinogenesis studies.
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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.