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dc.contributor.authorGrolmusz, Vince I.en_US
dc.date.accessioned2016-07-18T06:49:10Z
dc.date.available2016-07-18T06:49:10Z
dc.date.issued2015en_US
dc.identifier.otherHPU4160444en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/22288en_US
dc.description.abstractDiabetes is a growing concern for the developed nations worldwide. New genomic, metagenomic and gene-technologic approaches may yield considerable results in the next several years in its early diagnosis, or in advances in therapy and management. In this work, we highlight some human proteins that may serve as new targets in the early diagnosis and therapy. With the help of a very successful mathematical tool for network analysis that formed the basis of the early successes of GoogleTM we analyse the human protein–protein interaction network gained from the IntAct database with a mathematical algorithm.en_US
dc.format.extent8 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectComputer scienceen_US
dc.subjectBioinformaticsen_US
dc.subjectComputational biologyen_US
dc.subjectProtein interaction databaseen_US
dc.subjectInteractomeen_US
dc.subjectRelativizeden_US
dc.subjectPageRanken_US
dc.titleIdentifying diabetes-related important protein targets with few interacting partners with the PageRank algorithmen_US
dc.typeArticleen_US
dc.size327KBen_US
dc.departmentEducationen_US


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