Predicting stage-specific cancer related genes and their dynamic modules by integrating multiple datasets

Chaima Aouiche, Bolin Chen, Xuequn Shang

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

Background: The mechanism of many complex diseases has not been detected accurately in terms of their stage evolution. Previous studies mainly focus on the identification of associations between genes and individual diseases, but less is known about their associations with specific disease stages. Exploring biological modules through different disease stages could provide valuable knowledge to genomic and clinical research. Results: In this study, we proposed a powerful and versatile framework to identify stage-specific cancer related genes and their dynamic modules by integrating multiple datasets. The discovered modules and their specific-signature genes were significantly enriched in many relevant known pathways. To further illustrate the dynamic evolution of these clinical-stages, a pathway network was built by taking individual pathways as vertices and the overlapping relationship between their annotated genes as edges. Conclusions: The identified pathway network not only help us to understand the functional evolution of complex diseases, but also useful for clinical management to select the optimum treatment regimens and the appropriate drugs for patients.

源语言英语
文章编号194
期刊BMC Bioinformatics
20
DOI
出版状态已出版 - 1 5月 2019

指纹

探究 'Predicting stage-specific cancer related genes and their dynamic modules by integrating multiple datasets' 的科研主题。它们共同构成独一无二的指纹。

引用此