Browsing by Subject "Models, Statistical"

Now showing 1 - 4 of 4
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    Determination of the genetic relationships between wild olive (Olea europaea oleaster) varieties grown in the aegean region
    (Fundacao de Pesquisas Cientificas de Ribeirao Preto, 2010) Sesli M.; Yeǧenoǧlu E.D.
    The RAPD technique was used for determining genetic differences between 12 wild-olive varieties grown in the Aegean provinces of Izmir, Mugla, and Manisa in Turkey. Wild olives obtained from the same provinces were included in the same plot. Twenty of 25 operon primers (OP-I 4, OP-I 14, OP-I 15, OP-I 16, OP-I 17, OP-Q1, OP-Q2, OP-Q3, OP-Q4, OP-Q11, OP-Q12, OP-Q13, OP-Q14, OP-Q15, OP-Q16, OP-Q17, OP-Q18, OP-Q19, OP-Q20, OP-F1, OP-F2, OP-F3, OP-F6, OP-F7, OP-F8) yielded bands. The differences between the varieties were determined based on their genetic similarities, using principal coordinate analysis; genetic distances were determined using neighbor-joining analysis. The varieties wild 7 and wild 12 had the lowest genetic similarity (0.97, Jaccard similarity index); they also had the greatest genetic distance between them (0.3606, Nei's genetic distance). It was concluded that the RAPD technique is adequate for the evaluation of genetic relationships among wild olives. Principal coordinate analysis and neighbor-joining analysis gave results that support the Genetic relationships between wild olive varietie use of this type of analysis to help understand the genetic background of olives and for further genetic studies. ©FUNPEC-RP.
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    Hybrid imbalanced data classifier models for computational discovery of antibiotic drug targets
    (Institute of Electrical and Electronics Engineers Inc., 2014) Kocyigit Y.; Seker H.
    Identification of drug candidates is an important but also difficult process. Given drug resistance bacteria that we face, this process has become more important to identify protein candidates that demonstrate antibacterial activity. The aim of this study is therefore to develop a bioinformatics approach that is more capable of identifying a small but effective set of proteins that are expected to show antibacterial activity, subsequently to be used as antibiotic drug targets. As this is regarded as an imbalanced data classification problem due to smaller number of antibiotic drugs available, a hybrid classification model was developed and applied to the identification of antibiotic drugs. The model was developed by taking into account of various statistical models leading to the development of six different hybrid models. The best model has reached the accuracy of as high as 50% compared to earlier study with the accuracy of less than 1% as far as the proportion of the candidates identified and actual antibiotics in the candidate list is concerned. © 2014 IEEE.
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    Modification of the radial beam port of ITU TRIGA Mark II research reactor for BNCT applications
    (Elsevier Ltd, 2015) Akan Z.; Türkmen M.; Çakir T.; Reyhancan T.A.; Çolak T.; Okka M.; Kiziltaş S.
    This paper aims to describe the modification of the radial beam port of ITU (Istanbul Technical University) TRIGA Mark II research reactor for BNCT applications. Radial beam port is modified with Polyethylene and Cerrobend collimators. Neutron flux values are measured by neutron activation analysis (Au-Cd foils). Experimental results are verified with Monte Carlo results. The results of neutron/photon spectrum, thermal/epithermal neutron flux, fast group photon fluence and change of the neutron fluxes with the beam port length are presented. © 2015 Elsevier Ltd.
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    Capacity Evaluation of Diagnostic Tests for COVID-19 Using Multicriteria Decision-Making Techniques
    (Hindawi Limited, 2020) Sayan M.; Sarigul Yildirim F.; Sanlidag T.; Uzun B.; Uzun Ozsahin D.; Ozsahin I.
    In December 2019, cases of pneumonia were detected in Wuhan, China, which were caused by the highly contagious coronavirus. This study is aimed at comparing the confusion regarding the selection of effective diagnostic methods to make a mutual comparison among existing SARS-CoV-2 diagnostic tests and at determining the most effective one. Based on available published evidence and clinical practice, diagnostic tests of coronavirus disease (COVID-19) were evaluated by multi-criteria decision-making (MCDM) methods, namely, fuzzy preference ranking organization method for enrichment evaluation (fuzzy PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS). Computerized tomography of chest (chest CT), the detection of viral nucleic acid by polymerase chain reaction, cell culture, CoV-19 antigen detection, CoV-19 antibody IgM, CoV-19 antibody IgG, and chest X-ray were evaluated by linguistic fuzzy scale to compare among the diagnostic tests. This scale consists of selected parameters that possessed different weights which were determined by the experts' opinions of the field. The results of our study with both proposed MCDM methods indicated that the most effective diagnosis method of COVID-19 was chest CT. It is interesting to note that the methods that are consistently used in the diagnosis of viral diseases were ranked in second place for the diagnosis of COVID-19. However, each country should use appropriate diagnostic solutions according to its own resources. Our findings also show which diagnostic systems can be used in combination. © 2020 Murat Sayan et al.