Network-Based Method for Identifying Co-Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues

Abstract

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein–protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1

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Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer

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Investigation of miRNA and mRNA Co-expression Network in Ependymoma

“…In silico technology greatly improves the efficiency of our research on molecular mechanisms and biological functions (Li et al, 2019b;Pan et al, 2019b;Yuan et al, 2019). Theoretical models of system biology provide reliable support for finding mechanisms of molecular interaction (Chen et al, 2017(Chen et al, , 2018(Chen et al, , 2019Liu et al, 2017b;Li et al, 2018). The large data sets of both mRNA and miRNA expression profiles in the same patient could help discover the molecular mechanisms of miRNA-mRNA dysfunctions (Huang et al, 2015(Huang et al, , 2016Chen et al, 2016;Liu et al, 2017a;Zhou et al, 2019).…”