SynthesisBioMed research international2015
Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach.
Synthesis in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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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.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Glabridin ameliorates oxidative stress and inflammation in a bovine intestinal cell line and a colitis mouse model.Iranian journal of veterinary research · 2025Article
- Multi-omics integration reveals potential stage-specific druggable targets in T-cell acute lymphoblastic leukemia.Genes & diseases · 2024Article
- Targeting Mitochondrial Network Disorganization is Protective inAging and disease · 2021Article
- Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.Oncotarget · 2017Article
- Is the average shortest path length of gene set a reflection of their biological relatedness?Journal of bioinformatics and computational biology · 2016Article
- Transcriptome sequencing reveals aberrant alternative splicing in Huntington's disease.Human molecular genetics · 2016Article
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurodegenerative diseases (NDs), such as Parkinson's disease (PD) and Huntington's disease (HD), have become more and more common among aged people worldwide. One hallmark of NDs is the presence of intracellular accumulation of specific pathogenic proteins that may result from abnormal function of metabolic processes. Previously, we have developed a computational method named Met-express that predicted key enzyme-coding genes in cancer development by integrating cancer gene coexpression network with the metabolic network. Here, we applied Met-express to predict key enzyme-coding genes in both PD and HD. Functional enrichment analysis and literature review of predicted genes suggested that there might be some common pathogenic metabolic pathways for PD and HD. We further found that the predicted genes had significant functional association with known disease genes, with some of them already documented as biomarkers or therapeutic targets for NDs. As such, the predicted metabolic genes may be of use as novel biomarkers not only for ND diagnosis but also for potential therapeutic treatments.
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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.