ArticleIET systems biology2019
Mining conditions specific hub genes from RNA-Seq gene-expression data via biclustering and their application to drug discovery.
Article in IET systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Construction of a Pearson- and MIC-Based Co-expression Network to Identify Potential Cancer Genes.Interdisciplinary sciences, computational life sciences · 2022Article
- Identification of 40S ribosomal protein S8 as a novel biomarker for alcohol‑associated hepatocellular carcinoma using weighted gene co‑expression network analysis.Oncology reports · 2020Observational
- Efficient prediction of drug-drug interaction using deep learning models.IET systems biology · 2020Article
- Cucurbitacin E Inhibits Huh7 Hepatoma Carcinoma Cell Proliferation and Metastasis via Suppressing MAPKs and JAK/STAT3 Pathways.Molecules (Basel, Switzerland) · 2020Article
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Authors and funding
2 authors.
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Abstract
Gene-expression data is being widely used for various clinical research. It represents expression levels of thousands of genes across the various experimental conditions simultaneously. Mining conditions specific hub genes from gene-expression data is a challenging task. Conditions specific hub genes signify the functional behaviour of bicluster across the subset of conditions and can act as prognostic or diagnostic markers of the diseases. In this study, the authors have introduced a new approach for identifying conditions specific hub genes from the RNA-Seq data using a biclustering algorithm. In the proposed approach, efficient 'runibic' biclustering algorithm, the concept of gene co-expression network and concept of protein-protein interaction network have been used for getting better performance. The result shows that the proposed approach extracts biologically significant conditions specific hub genes which play an important role in various biological processes and pathways. These conditions specific hub genes can be used as prognostic or diagnostic biomarkers. Conditions specific hub genes will be helpful to reduce the analysis time and increase the accuracy of further research. Also, they summarised application of the proposed approach to the drug discovery process.
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Registered trials
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