Biyolojik Veri Tabanları

2018-01-01
YAGIZ, AYTEN KÜBRA
YAVUZ, CANER
Aksoy, Emre

Suggestions

Graphical models in inference of biological networks
Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda; Department of Statistics (2020)
In recent years, particularly, on the studies about the complex system’s diseases, better understanding the biological systems and observing how the system’s behaviors, which are affected by the treatment or similar conditions, accelerate with the help of the explanation of these systems via the mathematical modeling. Gaussian Graphical Models (GGM) is a model that describes the relationship between the system’s elements via the regression and represents the states of the system via the multivariate Gaussia...
Biyolojik Ağların Gaussian Grafiksel Modellerle Tahmininde Kopulaların Uygulanması ve Parametre Tahmini
Leon, De Alexander; Şeker, Tamay; Gazi, Parutçuoğlu Vilda; Wit, Ernst(2017)
Proje gerçekçi büyüklükteki karmasık biyolojik ag yapılarının sistem davranıslarını duraganhaldeyken modellenmesi ve model parametrelerinin Bayesci yaklasımlarla tahmin edilmesinikapsamaktadır. Modellemede kopula Gauassin grafiksel modeli (CGGM) kulanılmıs veparametre tahmini iseöncelikli olarak ters atlamalı Markov zinciri Monte Carlo yöntemiyleyapılmıstır.
Detection of the distribution and parameter estimation for the departing connectivity in biological networks
Odunsi, Omolola Dorcas; Purutçuoğlu Gazi, Vilda; Department of Statistics (2014)
The connectivity density is one of the characteristics features in the topology of the network. This density describes the total number of the in-degree and out-degree of a node in a system. In a network, the in-degree or arriving connectivity represents the number of links coming to a target gene and the out-degree or departing connectivity stands for the number of links departing from the target gene. For biological networks, the density of the in-degree is represented by the exponential distribution and ...
Heparin coated and 2-deoxy-d-glucose conjugated iron oxide nanoparticles for biologic applications /
Akpınar, Yeliz; Özçubukçu, Salih; Department of Chemistry (2017)
Over the past decade, there has been an increasing interest in using nanotechnology for cancer therapy. Magnetic-based systems containing magnetic nanoparticles have gained popularity because of their unique ability to be used in magnetic resonance imaging, magnetic targeting, drug carrying and hyperthermia. The last one represents a novel therapeutic concept to cancer treatmentIn biomedical and clinical applications the most commonly used magnetic nanomaterials are the iron oxide nanoparticles. Current pro...
Biyolojik Ağlar
YAGIZ, AYTEN KÜBRA; YAVUZ, CANER; Aksoy, Emre (PEGEM, 2020-01-01)
Citation Formats
A. K. YAGIZ, C. YAVUZ, and E. Aksoy, Biyolojik Veri Tabanları. 2018.