Stability Analysis of Biological Networks' Diffusion State

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dc.authorid0000-0003-3144-8724en_US
dc.contributor.authorAltuntaş, Volkan
dc.contributor.authorGok, Murat
dc.contributor.authorKahveci, Tamer
dc.date.accessioned2021-03-20T20:09:23Z
dc.date.available2021-03-20T20:09:23Z
dc.date.issued2020
dc.departmentBTÜ, Rektörlüğe Bağlı Birimler, Bilgi İşlem Daire Başkanlığıen_US
dc.description.abstractComputational knowledge acquired from noisy networks is not reliable and the network topology determines the reliability. Protein-protein interaction networks have uncertain topologies and noise that contain false positive and false negative edges at high rates. In this study, we analyze effects of the existing mutations in a network topology to the diffusion state of that network. To evaluate the sensitivity of the diffusion state, we derive the fitness measures based on the mathematically defined stability of a network. Searching for an influential set of edges in a network is a difficult problem. We handle the computational challenge by developing a novel metaheuristic optimization method and we find influential mutations time-efficiently. Our experiments, conducted on both synthetic and real networks from public databases, demonstrated that our method obtained better results than competitors for all types of network topologies. This is the first-time that the diffusion has been evaluated under topological mutations. Our analysis identifies significant biological results about the stability of biological - synthetic networks and diffusion state. In this manner, mutations in protein-protein interaction network topologies have a significant influence on the diffusion state of the network. Network stability is more affected by the network model than the network size.en_US
dc.description.sponsorshipBursa Technical UniversityBursa Technical University; Department of Science Fellowship and Grant programs of The Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [2219-2015]en_US
dc.description.sponsorshipThis study is a part of the Ph.D. thesis of the corresponding author in the Computer Engineering Department of Yalova University. This work was supported by the Bursa Technical University and the Department of Science Fellowship and Grant programs (2219-2015) of The Scientific and Technological Research Council of Turkey (TUBITAK). The authors have no conflict of interest to declare.en_US
dc.identifier.doi10.1109/TCBB.2018.2881887en_US
dc.identifier.endpage1418en_US
dc.identifier.issn1545-5963
dc.identifier.issn1557-9964
dc.identifier.issue4en_US
dc.identifier.pmid30452376en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1406en_US
dc.identifier.urihttp://doi.org/10.1109/TCBB.2018.2881887
dc.identifier.urihttps://hdl.handle.net/20.500.12885/398
dc.identifier.volume17en_US
dc.identifier.wosWOS:000556777900028en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorAltuntaş, Volkan
dc.language.isoenen_US
dc.publisherIeee Computer Socen_US
dc.relation.ispartofIeee-Acm Transactions On Computational Biology And Bioinformaticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSynthetic Networksen_US
dc.subjectBiological Networksen_US
dc.subjectDiffusionen_US
dc.subjectMutationsen_US
dc.subjectStabilityen_US
dc.subjectOptimizationen_US
dc.titleStability Analysis of Biological Networks' Diffusion Stateen_US
dc.typeArticleen_US

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