A New Mining Algorithm of Target Genes of Anti-Aging Traditional Chinese Medicines with Complex Networks

Title:A New Mining Algorithm of Target Genes of Anti-Aging Traditional Chinese Medicines with Complex Networks

Volume: 10 Issue: 1

Author(s): Jiang Qi-Yu, Sun Xiao-Sheng and Xu Feng

Affiliation:

Keywords: Anti-aging, complex networks, target genes, traditional Chinese medicines.

Abstract: GO (Gene Ontology) analysis is a technology which shows the enrichment and distribution of genes based on Gene Ontology databases. It has been widely used in the researches on target genes of biological compounds and medicines. However, the associations among target genes, as well as the associations among biological processes, molecular functions and cellular components were not cleared by the enrichment and distribution of target genes in GO(Gene Ontology) analysis. In this study, a new mining algorithm with complex network is given to solve the two problems by the analysis of target genes of anti-aging traditional Chinese medicines. All the data of effective ingredients and target genes for Chinese medicines in this study has been obtained from the databases: HIT, CNPD and TTD. The results show that, the synergistic processes for the target genes of antiaging traditional Chinese medicines may include: “response to stress - response to stimulus - response to chemical stimulus”, “immune system process - positive regulation of immune system process - regulation of immune system process”, and “regulation of apoptosis - negative regulation of apoptosis - regulation of programmed cell death”. The target genes which may play important roles in anti-aging include: NOS2A, PTGS2, CASP3, NFKB3, TNFA, SOD1, IL1B, and BCL2. The target genes with high association and synergies may include: “NOS2A-SOD1”, “BCL2-BAX”, “CASP3-NOS2A”, and “CASP3-NFkB3”.

Cite this article as:

Qi-Yu Jiang, Xiao-Sheng Sun and Feng Xu, A New Mining Algorithm of Target Genes of Anti-Aging Traditional Chinese Medicines with Complex Networks, Current Bioinformatics 2015; 10 (1) . https://dx.doi.org/10.2174/1574893609666140820224233