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dc.contributor.authorHabiboğlu, Mehmet Gökhan
dc.contributor.authorHernandez, Helen W.
dc.contributor.authorUyaver, Şahin
dc.date.accessioned2022-05-18T11:18:52Z
dc.date.available2022-05-18T11:18:52Z
dc.date.issued2022en_US
dc.identifier.citationHabiboğlu, M. G., Hernandez, H. W., & Uyaver, Ş. (2022). Shape investigations of structures formed by the self-assembly of aromatic amino acids using the density-based spatial clustering of applications with noise algorithm. Turkish Journal of Electrical Engineering & Computer Sciences, 30(1), 200-215.en_US
dc.identifier.issn1303-6203
dc.identifier.urihttps://hdl.handle.net/20.500.12846/650
dc.description.abstractTyrosine, tryptophan, and phenylalanine are important aromatic amino acids for human health. If they are not properly metabolized, severe rare mental or metabolic diseases can emerge, many of which are not researched enough due to economic priorities. In our previous simulations, all three of these amino acids are discovered to be self-organizing and to have complex aggregations at different temperatures. Two of these essential stable formations are observed during our simulations: tubular-like and spherical-like structures. In this study, we develop and implement a clustering analyzing algorithm using density-based spatial clustering of applications with noise (DBSCAN) to measure the shapes of the formed structures by the self-assembly processes of these amino acids. We present the results in quantitative and qualitative ways. To the best of our knowledge, the geometric shapes of the formed structures by the self-assembly processes of these amino acids are not measured quantitatively in the literature. Analytical measurements and comparisons of these aggregations might help us to identify the self-aggregations quickly at early stages in our simulations and hence provide us with more opportunity to experiment with different parameters of the molecular simulations (like temperature, mixture rates, and density). We first implement the DBSCAN method to identify the main self-aggregation cluster and then we develop and implement two algorithms to measure the shapes of the formed structures by the self-assembly processes of these amino acids. The measurements, which are completely in line with our simulation results, are presented in quantitative and qualitative ways.en_US
dc.language.isoengen_US
dc.publisherScientific & Technical Research Council Turkey-TUBITAKen_US
dc.relation.isversionof10.3906/elk-2003-144en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectClustering Analysisen_US
dc.subjectDensity-Based Spatial Clustering Of Applications With Noiseen_US
dc.subjectSelf Assemblyen_US
dc.subjectAmino Acidsen_US
dc.subjectSphericityen_US
dc.subjectCylindricityen_US
dc.subjectClusteranalyseen_US
dc.subjectSelbstmontageen_US
dc.subjectAminosäurenen_US
dc.subjectSphärizitäten_US
dc.subjectZylindrizitäten_US
dc.titleShape investigations of structures formed by the self-assembly of aromatic amino acids using the density-based spatial clustering of applications with noise algorithmen_US
dc.typearticleen_US
dc.relation.journalTurkish Journal of Electrical Engineering And Computer Sciencesen_US
dc.contributor.authorID0000-0002-8334-7944en_US
dc.identifier.volume30en_US
dc.identifier.issue1en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.departmentTAÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.institutionauthorHabiboğlu, Mehmet Gökhan
dc.contributor.institutionauthorUyaver, Şahin
dc.identifier.startpage200en_US
dc.identifier.endpage215en_US


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