Reconstruction of Gene Regulatory Networks

Chen, Luonan; Wang, Rui‐Sheng; Zhang, Xiang‐Sun

doi:10.1002/9780470488065.ch3

Cited by 11 publications

(2 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, a gene is inclined to interact with other genes, and the co-operated genes often actively participate in the same biological processes. Moreover, network-based approach is able to extract informative and significant genes dependent upon bio-molecular networks and provides a quantifiable characterization of the molecular networks that characterize the complicated interplays and the complex interwoven associations that administer cellular functions (25,26). Thus, a network was constructed on the informative genes, termed with MIN.…”

Section: Discussionmentioning

confidence: 99%

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

et al. 2018

View full text Add to dashboard Cite

Postmenopausal osteoporosis (PO) imposes great burden on individuals and society. This study predicted hub genes and gene functions for PO by an integration of the convergent evidence (CE) method, rank product (RP) algorithm and the combing of P-values. Using the gene expression data, genes were ranked by the CE method, RP algorithm and combing P-values, respectively. Subsequently, the top 100 genes were selected from each of the three gene lists, and then the common genes for two or three methods were denoted as informative genes of PO. A mutual information network (MIN) was constructed for the informative genes utilizing the context likelihood of relatedness algorithm. Topological centrality (degree) analysis was conducted on the MIN to investigate hub genes. Then we performed Gene Ontology (GO) enrichment analysis dependent upon the Biological Networks Gene Ontology tool (BiNGO) plugin of Cytoscape to investigate hub gene functions for PO patients. Consequently, a total of 82 informative genes were obtained by integrating the results of the three methods. There were 82 nodes and 1,741 edges in the MIN, of which 8 hub genes were identified, such as PFN1, EEF2 and S100A9. The result of GO enrichment analysis showed that 49 GO terms with P<0.001 were detected, especially the top 5 gene sets were defined as hub gene functions of PO, for instance, translational elongation, translation and cellular macromolecule biosynthetic process. In conclusion, we have predicted 8 hub genes and 5 hub gene functions associated with PO patients. The findings might help understand the molecular mechanism underlying PO.

show abstract

Section: Discussionmentioning

confidence: 99%

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

et al. 2018

View full text Add to dashboard Cite

show abstract

“…A network-based approach is capable of extracting informative and notable genes dependent on biomolecular networks. For instance, a protein-protein interaction network, co-expression network and mutual information network (MIN) rather than individual genes (8,9). …”

Section: Introductionmentioning

confidence: 99%

Combining affinity propagation clustering and mutual information network to investigate key genes in fibroid

Chen

Wang

Liu

et al. 2017

Experimental and Therapeutic Medicine

View full text Add to dashboard Cite

The aim of the present study was to investigate key genes in fibroids based on the multiple affinity propogation-Krzanowski and Lai (mAP-KL) method, which included the maxT multiple hypothesis, Krzanowski and Lai (KL) cluster quality index, affinity propagation (AP) clustering algorithm and mutual information network (MIN) constructed by the context likelihood of relatedness (CLR) algorithm. In order to achieve this goal, mAP-KL was initially implemented to investigate exemplars in fibroid, and the maxT function was employed to rank the genes of training and test sets, and the top 200 genes were obtained for further study. In addition, the KL cluster index was applied to determine the quantity of clusters and the AP clustering algorithm was conducted to identify the clusters and their exemplars. Subsequently, the support vector machine (SVM) model was selected to evaluate the classification performance of mAP-KL. Finally, topological properties (degree, closeness, betweenness and transitivity) of exemplars in MIN constructed according to the CLR algorithm were assessed to investigate key genes in fibroid. The SVM model validated that the classification between normal controls and fibroid patients by mAP-KL had a good performance. A total of 9 clusters and exemplars were identified based on mAP-KL, which were comprised of CALCOCO2, COL4A2, COPS8, SNCG, PA2G4, C17orf70, MARK3, BTNL3 and TBC1D13. By accessing the topological analysis for exemplars in MIN, SNCG and COL4A2 were identified as the two most significant genes of four types of methods, and they were denoted as key genes in the progress of fibroid. In conclusion, two key genes (SNCG and COL4A2) and 9 exemplars were successfully investigated, and these may be potential biomarkers for the detection and treatment of fibroid.

show abstract

Investigating ego modules involved in TGFβ3-induced chondrogenesis in mesenchymal stem cells based on ego network

Jia

et al. 2016

Computational Biology and Chemistry

View full text Add to dashboard Cite

Reconstruction of Gene Regulatory Networks

Cited by 11 publications

References 75 publications

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

Combining affinity propagation clustering and mutual information network to investigate key genes in fibroid

Investigating ego modules involved in TGFβ3-induced chondrogenesis in mesenchymal stem cells based on ego network

Contact Info

Product

Resources

About