ArticleDiabetes technology & therapeutics2015
Network Cluster Analysis of Protein-Protein Interaction Network-Identified Biomarker for Type 2 Diabetes.
Article in Diabetes technology & therapeutics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 14 citations in OpenAlex.
- Nutrient metabolism and complications of type 2 diabetes mellitus: implications for rehabilitation and precision care.Frontiers in nutrition · 2025Review
- A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023Article
- A cluster of blood-based protein biomarkers reflecting coagulation relates to the burden of cerebral small vessel disease.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022Article
- A systems biology-driven approach to construct a comprehensive protein interaction network of influenza A virus with its host.BMC infectious diseases · 2020Article
- Genome-wide profiling of mRNA and lncRNA expression in dengue fever and dengue hemorrhagic fever.FEBS open bio · 2019Article
- Multi-Level Comparative Framework Based on Gene Pair-Wise Expression Across Three Insulin Target Tissues for Type 2 Diabetes.Frontiers in genetics · 2019Article
- RETRACTED: An improved DBSCAN algorithm based on cell-like P systems with promoters and inhibitors.PloS one · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Type 2 diabetes mellitus (T2DM) is a complex disease that is caused by an impairment in the secretion of β-cell insulin and by a peripheral resistance to insulin. Most patients suffering from T2DM and from obesity exhibit insulin resistance in the muscles, liver, and fat, resulting in a reduced response of these tissues to insulin. In healthy individuals, pancreatic islet β-cells secrete insulin to regulate the increase in blood glucose levels. Once these β-cells fail to function, T2DM develops. Despite the progress achieved in this field in recent years, the genetic causes for insulin resistance and for T2DM have not yet been fully discovered. The present study aims to characterize T2DM by comparing its gene expression with that of normal controls, as well as to identify biomarkers for early T2DM. Gene expression profiles were downloaded from the Gene Expression Omnibus, and differentially expressed genes (DEGs) were identified for type 2 diabetes. Furthermore, functional analyses were conducted for the gene ontology and for the pathway enrichment. In total, 781 DEGs were identified in the T2DM samples relative to healthy controls. These genes were found to be involved in several biological processes, including cell communication, cell proliferation, cell shape, and apoptosis. We constructed a protein-protein interaction (PPI) network, and the clusters in the PPI were analyzed by using ClusterONE. Six functional genes that may play important roles in the initiation of T2DM were identified within the network.
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.