Co-expression network

Molecular-level effects of eribulin and paclitaxel on breast cancer based on differential co-expression network analysis

J. Qin, Chen, Y. H., Qin, J., and Chen, Y. H., “Molecular-level effects of eribulin and paclitaxel on breast cancer based on differential co-expression network analysis”, vol. 15, p. -, 2016.

We investigated the effects of eribulin and paclitaxel on breast cancer (BC) by exploring molecular biomarkers and pathways. Co-expression networks were constructed by differentially co-expressed genes and links, and centralities were analyzed to explore the hub genes. Pathway-enrichment analysis was performed. The hub genes were validated using the polymerase chain reaction and western blotting. A total of 132 and 153 differentially expressed genes were identified in BC cell lines treated with eribulin and paclitaxel, respectively.

Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis

Q. L. Wang, Chen, X., Zhang, M. H., Shen, Q. H., and Qin, Z. M., “Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis”, vol. 14, pp. 16151-16161, 2015.

The objective of this paper was to identify hub genes and pathways associated with retinoblastoma using centrality analysis of the co-expression network and pathway-enrichment analysis. The co-expression network of retinoblastoma was constructed by weighted gene co-expression network analysis (WGCNA) based on differentially expressed (DE) genes, and clusters were obtained through the molecular complex detection (MCODE) algorithm. Degree centrality analysis of the co-expression network was performed to explore hub genes present in retinoblastoma.

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