Research Article

Text-mining network analysis of the response to osmotic stimuli in the intervertebral disc

Published: May 13, 2013
Genet. Mol. Res. 12 (2) : 1574-1581 DOI: https://doi.org/10.4238/2013.May.13.11
Cite this Article:
X. Xu, L. Liu, Q.Y. Lu (2013). Text-mining network analysis of the response to osmotic stimuli in the intervertebral disc. Genet. Mol. Res. 12(2): 1574-1581. https://doi.org/10.4238/2013.May.13.11
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Abstract

Intervertebral disc cells experience a broad range of physical stimuli under physiologic conditions, including alterations in their osmotic environment. The purpose of this study was to construct a text-mining network of the genes induced during the response to osmotic stimuli in the intervertebral disc. We obtained a gene expression profile of human intervertebral disc cells from the National Center for Biotechnology Information, after culture under hyper- and hypo-osmotic conditions compared to iso-osmotic conditions, and we identified 65 differentially expressed genes of intervertebral disc cells. We constructed a text-mining network using Biblio-MetReS between the differentially expressed genes and other genes that were included in the same document as the differentially expressed genes. Then, we performed pathway-enrichment analysis to identify the most relevant pathways for the response to osmotic stimuli in intervertebral disc cells. Our data provide a comprehensive bioinformatics analysis of genes and pathways that may be involved in the response to osmotic stimuli in the intervertebral disc.

Intervertebral disc cells experience a broad range of physical stimuli under physiologic conditions, including alterations in their osmotic environment. The purpose of this study was to construct a text-mining network of the genes induced during the response to osmotic stimuli in the intervertebral disc. We obtained a gene expression profile of human intervertebral disc cells from the National Center for Biotechnology Information, after culture under hyper- and hypo-osmotic conditions compared to iso-osmotic conditions, and we identified 65 differentially expressed genes of intervertebral disc cells. We constructed a text-mining network using Biblio-MetReS between the differentially expressed genes and other genes that were included in the same document as the differentially expressed genes. Then, we performed pathway-enrichment analysis to identify the most relevant pathways for the response to osmotic stimuli in intervertebral disc cells. Our data provide a comprehensive bioinformatics analysis of genes and pathways that may be involved in the response to osmotic stimuli in the intervertebral disc.

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