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dc.contributor.authorDey, Lopamudra-
dc.contributor.authorMukhopadhyay, Anirban-
dc.date.accessioned2021-03-30T06:05:32Z-
dc.date.available2021-03-30T06:05:32Z-
dc.date.issued2020-05-
dc.identifier.urihttp://172.16.0.4:8085/heritage/handle/123456789/4849-
dc.description.abstractAbstract Dengue virus (DENV) is one of the deadly arboviruses, which is primarily transmitted by Aedes aegypti, and causes dengue infection to the humans. According to WHO, every year around 390 million humans are affected by DENV, of which around 50 million deaths are reported. Knowledge of the various diseases caused by the DENV would greatly encourage to understand the infection mechanism and help to design new antiviral drug discovery. We propose a quasi-clique and quasi-biclique algorithm to classify infection gateway proteins of the human body and possible pathways of DENV leading to various diseases. For this, we have examined three networks, dengue-human protein–protein interaction network, human protein interaction network, and human proteins-disease association network. The prediction result states that DENV may lead to various diseases in the human body, including cancer, asthma, ulcerative colitis, multiple sclerosis, premature birth, and so on. Some of the results have recently been validated experimentally. This study may endow with potential targets for more effective anti-dengue remedial contribution.en_US
dc.language.isoenen_US
dc.publisherMary Ann Liebert (Foreign)en_US
dc.relation.ispartofseriesVolume 27;No 5-
dc.subjectDengue virusen_US
dc.subjectDENVen_US
dc.subjectDengue-human proteinen_US
dc.subjectProtein interaction networken_US
dc.subjectInfection gatewayen_US
dc.titleA Graph-Based Approach for Finding the Dengue Infection Pathways in Humans Using Protein–Protein Interactionsen_US
dc.title.alternative(in) Journal of Computational Biologyen_US
dc.typeOtheren_US
Appears in Collections:Computer Application [MCA] (Publication)

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