Publication: An information theoretical analysis of human insulin-glucose system toward the internet of bio-nano things
dc.contributor.department | Department of Electrical and Electronics Engineering | |
dc.contributor.department | Graduate School of Sciences and Engineering | |
dc.contributor.kuauthor | Abbasi, Naveed Ahmed | |
dc.contributor.kuauthor | Akan, Özgür Barış | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.schoolcollegeinstitute | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
dc.date.accessioned | 2024-11-09T13:46:24Z | |
dc.date.issued | 2017 | |
dc.description.abstract | Molecular communication is an important tool to understand biological communications with many promising applications in Internet of Bio-Nano Things (IoBNT). The insulin-glucose system is of key significance among the major intra-body nanonetworks, since it fulfills metabolic requirements of the body. The study of biological networks from information and communication theoretical (ICT) perspective is necessary for their introduction in the IoBNT framework. Therefore, the objective of this paper is to provide and analyze for the first time in the literature, a simple molecular communication model of the human insulin-glucose system from ICT perspective. The data rate, channel capacity, and the group propagation delay are analyzed for a two-cell network between a pancreatic beta cell and a muscle cell that are connected through a capillary. The results point out a correlation between an increase in insulin resistance and a decrease in the data rate and channel capacity, an increase in the insulin transmission rate, and an increase in the propagation delay. We also propose applications for the introduction of the system in the IoBNT framework. Multi-cell insulin glucose system models may be based on this simple model to help in the investigation, diagnosis, and treatment of insulin resistance by means of novel IoBNT applications. | |
dc.description.fulltext | YES | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.issue | 8 | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | EU | |
dc.description.sponsorship | European Research Council (ERC) | |
dc.description.sponsorship | European Union (European Union) | |
dc.description.sponsorship | H2020 | |
dc.description.sponsorship | MINERVA | |
dc.description.sponsorship | CIRCLE | |
dc.description.version | Author's final manuscript | |
dc.description.volume | 16 | |
dc.identifier.doi | 10.1109/TNB.2017.2762160 | |
dc.identifier.embargo | NO | |
dc.identifier.filenameinventoryno | IR01590 | |
dc.identifier.issn | 1536-1241 | |
dc.identifier.quartile | Q2 | |
dc.identifier.scopus | 2-s2.0-85031941321 | |
dc.identifier.uri | https://doi.org/10.1109/TNB.2017.2762160 | |
dc.identifier.wos | 423238600017 | |
dc.keywords | Internet of Bio-Nano Things (IoBNT) | |
dc.keywords | Insulin-glucose system | |
dc.keywords | ICT-based modeling | |
dc.keywords | Molecular communication | |
dc.keywords | Insulin resistance | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.grantno | 616922 | |
dc.relation.grantno | 665564 | |
dc.relation.ispartof | IEEE Transactions on NanoBioscience | |
dc.relation.uri | http://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/8392 | |
dc.subject | Biochemistry and molecular biology | |
dc.subject | Science and technology | |
dc.title | An information theoretical analysis of human insulin-glucose system toward the internet of bio-nano things | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Abbasi, Naveed Ahmed | |
local.contributor.kuauthor | Akan, Özgür Barış | |
local.publication.orgunit1 | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Electrical and Electronics Engineering | |
local.publication.orgunit2 | Graduate School of Sciences and Engineering | |
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relation.isOrgUnitOfPublication | 3fc31c89-e803-4eb1-af6b-6258bc42c3d8 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 21598063-a7c5-420d-91ba-0cc9b2db0ea0 | |
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