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Analyzing the Protein-protein Interaction Network and the Topological Properties of Prostate Cancer and Allied Diseases

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dc.contributor.author Puspo, Nadira Akter
dc.contributor.author Akter, Laboni
dc.contributor.author Siddique, Sinthia
dc.contributor.author Paul, Bikash Kumar
dc.contributor.author Ahmed, Kawsar
dc.contributor.author Bhuiyan, Touhid
dc.contributor.author Islam, Md Kabirul
dc.date.accessioned 2022-01-08T08:40:00Z
dc.date.available 2022-01-08T08:40:00Z
dc.date.issued 2020
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6689
dc.description.abstract Background and objectives Some of cancer diseases are related to each other by their metabolic structures. Literature reviews show that Prostate Cancer (PC), Breast Cancer (BC), Bladder Cancer (BDC) and Colorectal Cancer (CRC) are related. Some are shown up for affected family background in their early or grown-up age. Materials and methods Python programming language is used for data mining, pre-processing and sorting and finding common genes from gathered data whose are collected National Centre of Biotechnology Information (NCBI). Protein-Protein Interaction (PPIs) and Protein Disease Interaction (PDI) are displayed by using bioinformatics technology. We use identified hub genes for making co-expression and physical interaction. Results Interactions for selected top 8 genes are exhibited following different bioinformatics tools. The gene-miRNA interaction generates interactions with a total of 651 links between 8 genes. Where, the TF-gene Interaction creates relationships between 176 nodes and 278 edges. There are 6 seed nodes. Besides, PDI represents a subnetwork which creates relationships between 47 nodes and 46 edges. There are 1 seed nodes. In addition, PCI creates relationships between 1437 nodes and 2165 edges. There are 7 seed nodes. Furthermore, GDA creates relationships between 235 nodes and 272 edges. There are 5 seed nodes. Conclusion This study will be helpful for further studies of different bioinformatics tools for designing gene network models and drugs design. These drugs can be considered for further verification by chemical experiments. en_US
dc.language.iso en_US en_US
dc.publisher Gene Reports, Science Direct, Elsevier en_US
dc.subject Computational bioinformatics en_US
dc.subject Prostate cancer en_US
dc.subject Breast cancer en_US
dc.subject Bladder cancer en_US
dc.subject Colorectal cancer en_US
dc.subject Protein-protein interaction network en_US
dc.title Analyzing the Protein-protein Interaction Network and the Topological Properties of Prostate Cancer and Allied Diseases en_US
dc.title.alternative A Computational Bioinformatics Approach en_US
dc.type Article en_US


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