Shape investigations of structures formed by the self-assembly of aromatic amino acids using the density-based spatial clustering of applications with noise algorithm

dc.authorid0000-0002-8334-7944
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.issued2022
dc.departmentTAÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
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.
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.
dc.identifier.doi10.3906/elk-2003-144
dc.identifier.endpage215en_US
dc.identifier.issn1303-6203
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85125867298
dc.identifier.scopusqualityQ3
dc.identifier.startpage200en_US
dc.identifier.trdizinid527862
dc.identifier.urihttps://hdl.handle.net/20.500.12846/650
dc.identifier.volume30en_US
dc.identifier.wosWOS:000746494300001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorHabiboğlu, Mehmet Gökhan
dc.institutionauthorUyaver, Şahin
dc.language.isoen
dc.publisherScientific & Technical Research Council Turkey-TUBITAK
dc.relation.ispartofTurkish Journal of Electrical Engineering And Computer Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
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 algorithm
dc.typeArticle

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