EnsemBic: An effective ensemble of biclustering to identify potential biomarkers of esophageal squamous cell carcinoma

The development of functionally enriched and biologically competent biclustering algorithm is essential for extracting hidden information from massive biological datasets. This paper presents a novel biclustering ensemble called EnsemBic based on p-value, which calculates the functional similarity o...

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Veröffentlicht in:Computational biology and chemistry 2024-06, Vol.110, p.108090-108090, Article 108090
Hauptverfasser: Baruah, Bikash, Dutta, Manash P., Banerjee, Subhasish, Bhattacharyya, Dhruba K.
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creator Baruah, Bikash
Dutta, Manash P.
Banerjee, Subhasish
Bhattacharyya, Dhruba K.
description The development of functionally enriched and biologically competent biclustering algorithm is essential for extracting hidden information from massive biological datasets. This paper presents a novel biclustering ensemble called EnsemBic based on p-value, which calculates the functional similarity of genetic associations. To validate the effectiveness and robustness of EnsemBic, we apply three well-known biclustering techniques, viz. Laplace Prior, iBBiG, and xMotif to implement EnsemBic and have been compared using different leading parameters. It is observed that the EnsemBic outperforms its competing algorithms in several prominent functional and biological measures. Next, the biclusters obtained from EnsemBic are used to identify potential biomarkers of Esophageal Squamous Cell Carcinoma (ESCC) by exploring topological and biological relevance with reference to the elite genes, attained from genecards. Finally, we discover that the genes F2RL3, APPL1, CALM1, IFNGR1, LPAR1, ANGPT2, ARPC2, CGN, CLDN7, ATP6V1C2, CEACAM1, FTL, PLAU,PSMB4, and EPHB2 carry both the topological and biological significance of previously established ESCC elite genes. Therefore, we declare the aforementioned genes as potential biomarkers of ESCC. [Display omitted] •EnsemBic exclusively comprises the high-quality biclusters obtained from the well-known base biclustering algorithms.•The biclusters extracted by EnsemBic undergo validation using prominent functional and biological measures, establishing their high functional and biological significance.•Topological analysis reveals the usefulness of extracted biclusters in identifying potential biomarkers of ESCC.•Validation through gene enrichment analysis and pathway exploration ensures the biological relevance and significance of the identified potential biomarkers.•A specialized literature survey substantiates the significance of the identified potential biomarkers responsible for ESCC.
doi_str_mv 10.1016/j.compbiolchem.2024.108090
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subjects Algorithms
Biclustering algorithm
Biological analysis
Biomarkers, Tumor - genetics
Cluster Analysis
Elite gene
Esophageal Neoplasms - genetics
Esophageal Squamous Cell Carcinoma - genetics
FuncAssociate
Humans
Potential biomarker
Topological analysis
title EnsemBic: An effective ensemble of biclustering to identify potential biomarkers of esophageal squamous cell carcinoma
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