Article: A functional network construction method to interpret the pathological process of colorectal cancer Journal: International Journal of Data Mining and Bioinformatics (IJDMB) 2020 Vol.23 No.3 pp.251 - 264 Abstract: The prognosis of cancers remains a challenge due to the limited understanding of their pathogenic mechanisms and cancerous processes. To overcome this, many studies employ a set of Differentially Expressed Genes (DEGs) to analyse the significant dysfunctions alone with the pathological stages. However, those studies often ignore the fact that DEGs detected from cancer patients tend to be highly heterogeneous with each other, which could easily mislead the enriched dysfunctions toward to those less relevant functions. Hence, in this study, we propose a novel method to generate the functional evolution network to describe the transferring processes of dysfunctions of the cancer. Results interpret that the proposed network construction method has a powerful capacity in detecting the most relevant cellular functions compared with existing methods, which could be employed to explore the evolution processes of cancers and may provide a new method for therapeutic intervention. Inderscience Publishers - linking academia, business and industry through research

Title: A functional network construction method to interpret the pathological process of colorectal cancer

Authors: Bolin Chen; Manting Yang; Li Gao; Tao Jiang; Xuequn Shang

Addresses: School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China ' School of Software, Northwestern Polytechnical University, Xi'an, Shaanxi, China ' School of Software, Northwestern Polytechnical University, Xi'an, Shaanxi, China ' School of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou, Henan, China ' School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China

Abstract: The prognosis of cancers remains a challenge due to the limited understanding of their pathogenic mechanisms and cancerous processes. To overcome this, many studies employ a set of Differentially Expressed Genes (DEGs) to analyse the significant dysfunctions alone with the pathological stages. However, those studies often ignore the fact that DEGs detected from cancer patients tend to be highly heterogeneous with each other, which could easily mislead the enriched dysfunctions toward to those less relevant functions. Hence, in this study, we propose a novel method to generate the functional evolution network to describe the transferring processes of dysfunctions of the cancer. Results interpret that the proposed network construction method has a powerful capacity in detecting the most relevant cellular functions compared with existing methods, which could be employed to explore the evolution processes of cancers and may provide a new method for therapeutic intervention.

Keywords: CRC; colorectal cancer; enrichment analysis; functional interaction network; functional evolution network.

DOI: 10.1504/IJDMB.2020.107879

International Journal of Data Mining and Bioinformatics, 2020 Vol.23 No.3, pp.251 - 264

Received: 10 Apr 2020
Accepted: 10 Apr 2020
Published online: 26 Jun 2020 *

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Title: A functional network construction method to interpret the pathological process of colorectal cancer

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