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- Title
PD_BiBIM: Biclustering-based biomarker identification in ESCC microarray data.
- Authors
Patowary, Pallabi; Bhattacharyya, Dhruba K.
- Abstract
To promote diligent analysis of the progression of a disease, it is important to identify interesting biomarkers for the disease. Biclustering has already been established as an effective technique to help identify such biomarkers of high biological significance. Although in the recent past, a good number of biclustering techniques have been introduced, most of them fail to perform consistently across multiple domains or datasets. To choose a single biclustering technique that can help the accomplishment of such a critical task for multiple diseases with high precision is extremely difficult. Hence, in this study, we considered several biclustering techniques and accepted those techniques and their results which are found significant from enrichment perspective for subsequent analysis. Based on biclustering results, we constructed biological networks and carried out a topological, pathway and causal analysis on the modules extracted from the networks. Our multi-objective study enabled us to identify several biomarkers for esophageal squamous cell carcinoma (ESCC) such as IFNGR1, CLIC1, CDK4, and COPS5, after applying a ranking scheme.
- Subjects
BIOMARKERS; BIOLOGICAL networks; SQUAMOUS cell carcinoma; DISEASE progression
- Publication
Journal of Biosciences, 2021, Vol 46, Issue 3, p1
- ISSN
0250-5991
- Publication type
Article
- DOI
10.1007/s12038-021-00171-5