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    • Keywords


      Co-expression network; ESCC biomarker; ESCC disease; microarray data; primary gene; secondary gene

    • Abstract


      To promote diligent analysis of the progression of a disease, it is important to identify interesting biomarkersfor the disease. Biclustering has already been established as an effective technique to help identify suchbiomarkers of high biological significance. Although in the recent past, a good number of biclustering techniqueshave been introduced, most of them fail to perform consistently across multiple domains or datasets. Tochoose a single biclustering technique that can help the accomplishment of such a critical task for multiplediseases with high precision is extremely difficult. Hence, in this study, we considered several biclusteringtechniques and accepted those techniques and their results which are found significant from enrichmentperspective for subsequent analysis. Based on biclustering results, we constructed biological networks andcarried out a topological, pathway and causal analysis on the modules extracted from the networks. Our multiobjectivestudy enabled us to identify several biomarkers for esophageal squamous cell carcinoma (ESCC)such as IFNGR1, CLIC1, CDK4, and COPS5, after applying a ranking scheme.

    • Author Affiliations



      1. Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam, India
    • Dates

  • Journal of Biosciences | News

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      Posted on July 25, 2019

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