Abstract
Liver hepatocellular carcinoma (LIHC) is the most common primary malignancy of the liver and is one of the primary contributors to cancer-related death worldwide. The present work proposed a computational framework to discover functional gene communities in LIHC by integrating RNASeq gene expression profiles with protein-protein interaction data to elucidate the inherent complexities of biomolecular mechanisms in LIHC. Here, we have proposed an offsetNMF-based module integration technique that incorporates characteristics of both gene co-expression modules discovered through a refined WGCNA-based algorithm and protein complexes predicted through a parameter-free greedy approximation algorithm PC2P. Biological significance analysis of the integrated gene communities discovers several highly LIHC-associated pathways.
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Hossain, S.M.M., Halsana, A.A. (2022). Identification of Gene Communities in Liver Hepatocellular Carcinoma: An OffsetNMF-Based Integrative Technique. In: Hemanth, D.J., Pelusi, D., Vuppalapati, C. (eds) Intelligent Data Communication Technologies and Internet of Things. Lecture Notes on Data Engineering and Communications Technologies, vol 101. Springer, Singapore. https://doi.org/10.1007/978-981-16-7610-9_30
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