ArticleTheScientificWorldJournal2014
Gene expression profile analysis in epilepsy by using the partial least squares method.
Article in TheScientificWorldJournal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Uncovering the Pharmacological Mechanism ofEvidence-based complementary and alternative medicine : eCAM · 2019Article
- Altered Biogenesis and MicroRNA Content of Hippocampal Exosomes Following Experimental Status Epilepticus.Frontiers in neuroscience · 2019Article
- Developmental and Functional Brain Impairment in Offspring from Preeclampsia-Like Rats.Molecular neurobiology · 2016Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeEpilepsy is a common chronic neurological disorder. We aim to investigate the underlying mechanism of epilepsy with partial least squares- (PLS-) based gene expression analysis, which is more sensitive than routine variance/regression analysis.
methodsTwo microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database. PLS analysis was used to identify differentially expressed genes. Gene ontology and network analysis were also implemented.
resultsA total of 752 genes were identified to be differentially expressed, including 575 depressed and 177 overexpressed genes in patients. For GO enrichment analysis, except for processes related to the nervous system, we also identified overrepresentation of dysregulated genes in angiogenesis. Network analysis revealed two hub genes, CUL3 and EP300, which may serve as potential targets in further therapeutic studies.
conclusionOur results here may provide new understanding for the underlying mechanisms of epilepsy pathogenesis and will offer potential targets for producing new treatments.
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