Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method
Purpose. Epilepsy 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. Methods. Two microarray data sets were downloa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/731091 |
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| author | Dong Wang Xixiao Song Yan Wang Xia Li Shanshan Jia Zhijing Wang |
| author_facet | Dong Wang Xixiao Song Yan Wang Xia Li Shanshan Jia Zhijing Wang |
| author_sort | Dong Wang |
| collection | DOAJ |
| description | Purpose. Epilepsy 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. Methods. Two 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. Results. A 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. Conclusion. Our results here may provide new understanding for the underlying mechanisms of epilepsy pathogenesis and will offer potential targets for producing new treatments. |
| format | Article |
| id | doaj-art-fd57010d03e8460387e0b5d670d3ffba |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-fd57010d03e8460387e0b5d670d3ffba2025-02-03T01:28:42ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/731091731091Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares MethodDong Wang0Xixiao Song1Yan Wang2Xia Li3Shanshan Jia4Zhijing Wang5Department of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaDepartment of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaDepartment of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaDepartment of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaDepartment of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaDepartment of Neurology, Xi’an Children’s Hospital, Xi’an, Shaanxi 710003, ChinaPurpose. Epilepsy 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. Methods. Two 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. Results. A 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. Conclusion. Our results here may provide new understanding for the underlying mechanisms of epilepsy pathogenesis and will offer potential targets for producing new treatments.http://dx.doi.org/10.1155/2014/731091 |
| spellingShingle | Dong Wang Xixiao Song Yan Wang Xia Li Shanshan Jia Zhijing Wang Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method The Scientific World Journal |
| title | Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method |
| title_full | Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method |
| title_fullStr | Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method |
| title_full_unstemmed | Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method |
| title_short | Gene Expression Profile Analysis in Epilepsy by Using the Partial Least Squares Method |
| title_sort | gene expression profile analysis in epilepsy by using the partial least squares method |
| url | http://dx.doi.org/10.1155/2014/731091 |
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