ArticleJournal of healthcare engineering2021
Protein-Protein Interaction Analysis through Network Topology (Oral Cancer).
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 32 citations in OpenAlex.
- Genomic adaptability and virulence of Bacillus anthracis: a machine learning-based pan-genome and comparative analysis.BMC genomics · 2026Article
- Delineating CYP2C19-mediated Interactions: Network Pharmacology Investigation of Ilaprazole and ClopidogrelCurrent drug discovery technologies · 2025Article
- Overlap in oncogenic and pro-inflammatory pathways associated with areca nut and nicotine exposure.Cancer pathogenesis and therapy · 2024Article
- Efficacy of Ganshuang granules on non-alcoholic fatty liver and underlying mechanism: a network pharmacology and experimental verification.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2024Article
- Unravelling the Mystery inside Cells by Using Single-Molecule Fluorescence Imaging.Journal of imaging · 2023Review
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral cancer is a complex disorder. Its creation and spreading are due to the interaction of several proteins and genes in different biological thoroughfares. To study biological pathways, many high-yield methods have been used. Efforts to merge several data found at separate levels related to biological thoroughfares and interlinkage networks remain elusive. In our research work, we have proposed a technique known as protein-protein interaction network for analysis and exploring the genes involved in oral cancer disorders. The previous studies have not fully analyzed the proteins or genes involved in oral cancer. Our proposed technique is fully interactive and analyzes the data of oral cancer disorder more accurately and efficiently. The methods used here enabled us to observe the wide network consists of one mighty network comprising of 208 nodes 1572 edges which connect these nodes and various detached small networks. In our study, TP53 is a gene that occupied an important position in the network. TP53 has a 113-degree value and 0.03881821 BC value, indicating that TP53 is centrally localized in the network and is a significant bottleneck protein in the oral cancer protein-protein interaction network. These findings suggested that the pathogenesis of oral cancer variation was organized by means of an integrated PPI network, which is centered on TP53. Furthermore, our identification shows that TP53 is the key role-playing protein in the oral cancer network, and its significance in the cellular networks in the body is determined as well. As TP53 (tumor protein 53) is a vital player in the cell division process, the cells may not grow or divide disorderly; it fulfills the function of at least one of the gene groups in oral cancer. However, the latter progression in the area is any measure; the intention of developing these networks is to transfigure sketch of core disease development, prognosis, and treatment.
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