Uyar, Aslı
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Uyar Aslı
Aslı, Uyar
A., Uyar
Aslı Uyar
Aslı UYAR
UYAR Aslı
Uyar, A.
Uyar, Asli
Asli Uyar
Uyar Asli
Uyar A.
UYAR Asli
Asli UYAR
Uyar, Aslı
Aslı, Uyar
A., Uyar
Aslı Uyar
Aslı UYAR
UYAR Aslı
Uyar, A.
Uyar, Asli
Asli Uyar
Uyar Asli
Uyar A.
UYAR Asli
Asli UYAR
Uyar, Aslı
Job Title
Dr.Öğr.Üyesi
Email Address
asli.uyar@okan.edu.tr
ORCID ID
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Turkish CoHE Profile ID
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Scholarly Output
15
Articles
9
Citation Count
298
Supervised Theses
0
15 results
Scholarly Output Search Results
Now showing 1 - 10 of 15
Article Citation Count: 48Metabolomic Assessment of Embryo Viability(Thieme Medical Publ inc, 2014) Uyar, Asli; Seli, Emre; Bilgisayar Mühendisliği / Computer EngineeringPreimplantation embryo metabolism demonstrates distinctive characteristics associated with the developmental potential of embryos. On this basis, metabolite content of culture media was hypothesized to reflect the implantation potential of individual embryos. This hypothesis was tested in consecutive studies reporting a significant association between culture media metabolites and embryo development or clinical pregnancy. The need for a noninvasive, reliable, and rapid embryo assessment strategy promoted metabolomics studies in vitro fertilization (IVF) in an effort to increase success rates of single embryo transfers. With the advance of analytical techniques and bioinformatics, commercial instruments were developed to predict embryo viability using spectroscopic analysis of surplus culture media. However, despite the initial promising results from proof-of-principal studies, recent randomized controlled trials using commercial instruments failed to show a consistent benefit in improving pregnancy rates when metabolomics is used as an adjunct to morphology. At present, the application of metabolomics technology in clinical IVF laboratory requires the elimination of factors underlying inconsistent findings, when possible, and development of reliable predictive models accounting for all possible sources of bias throughout the embryo selection process.Article Citation Count: 0Rejection threshold optimization using 3D ROC curves: Novel findings on biomedical datasets(Ismail Saritas, 2021) Uyar,A.; Sengul,Y.A.; Bilgisayar Mühendisliği / Computer EngineeringReject option is introduced in classification tasks to prevent potential misclassifications. Although optimization of error-reject trade-off has been widely investigated, it is shown that error rate itself is not an appropriate performance measure, when misclassification costs are unequal or class distributions are imbalanced. ROC analysis is proposed as an alternative approach to performance evaluation in terms of true positives (TP) and false positives (FP). Considering classification with reject option, we need to represent the tradeoff between TP, FP and rejection rates. In this paper, we propose 3D ROC analysis to determine the optimal rejection threshold as an analogy to decision threshold optimization in 2D ROC curves. We have demonstrated our proposed method with Naive Bayes classifier on Heart Disease dataset and validated the efficiency of the method on multiple datasets from UCI Machine Learning Repository. Our experiments reveal that classification with optimized rejection threshold significantly improves true positive rates in biomedical datasets. Furthermore, false positive rates remain the same with rejection rates below 10% on average. © 2021, Ismail Saritas. All rights reserved.Conference Object Citation Count: 5AN ANALYSIS OF CONCURRENCE ENTANGLEMENT MEASURE AND QUANTUM FISHER INFORMATION OF QUANTUM COMMUNICATION NETWORKS OF TWO-QUBITS(Ieee, 2014) Erol, Volkan; Bugu, Sinan; Ozaydin, Fatih; Altintas, Azmi Ali; Bilgisayar Mühendisliği / Computer EngineeringQuantum entanglement is one of key concepts in quantum communication engineering. Ordering the quantum systems according to their entanglement measures is a popular problem of the field. For two level (qubit) systems of two particles, state ordering has been studied with respect to well-known entanglement measures such as Concurrence, Negativity and Relative Entropy of Entanglement (REE) [1-5]. In this work, we study the state ordering of the two-qubit systems with respect to Quantum Fisher Information vs. Concurrence. In particular, constructing 1K random states and calculating their Concurrences and Negativities, we obtain the orderings of the states by comparing these results with Quantum Fisher Information values and present our results which are interesting when compared to that of two-level systems.Article Citation Count: 26Non-invasive assessment of embryonic sex in cattle by metabolic fingerprinting of in vitro culture medium(Springer, 2014) Munoz, Marta; Uyar, Asli; Correia, Eva; Diez, Carmen; Fernandez-Gonzalez, Alfonso; Nestor Caamano, Jose; Gomez, Enrique; Bilgisayar Mühendisliği / Computer EngineeringThe objective of this work was to determine whether metabolic fingerprinting of spent bovine embryo culture media using Fourier transform infrared spectroscopy (FTIR) correlates with embryonic sex. Embryos were produced in vitro from oocytes collected from cows slaughtered in an abattoir. Day-6 embryos were individually cultured in synthetic oviduct fluid for 24 h, prior to the time (Day-7) intended for embryo transfer or cryopreservation. Culture medium was analyzed by FTIR. Embryos were sexed by a PCR procedure based on amelogenin gene amplification or transferred to a recipient and sex observed at birth. Media samples from embryos diagnosed as male (n = 47) or female (n = 70) were individually collected and evaluated using FTIR. The spectra obtained were analyzed according to metabolomic profile of embryo culture media and embryonic sex. The discrimination capability of the classifiers was assessed for accuracy, sensitivity (female), sensitivity (male) and area under the ROC curve (AUC). Performance of sex prediction (%) was high within early blastocysts + blastocysts (74.4 +/- A 10.2, accuracy; 0.749 +/- A 0.099, AUC) and excellent for expanded blastocysts (86.0 +/- A 12.6, accuracy; 0.898 +/- A 0.094, AUC). A combination of metabolomic and bioinformatic analysis provides a non-invasive mean of embryonic sex analysis.Article Citation Count: 42Prediction of pregnancy viability in bovine in vitro-produced embryos and recipient plasma with Fourier transform infrared spectroscopy(Elsevier Science inc, 2014) Munoz, M.; Uyar, A.; Correia, E.; Diez, C.; Fernandez-Gonzalez, A.; Caamano, J. N.; Gomez, E.; Bilgisayar Mühendisliği / Computer EngineeringWe analyzed embryo culture medium (CM) and recipient blood plasma using Fourier transform infrared (FTIR) metabolomics to predict pregnancy outcome. Individually cultured, in vitro-produced (IVP) blastocysts were transferred to recipients as fresh and vitrified-warmed. Spent CM and plasma samples were evaluated using FTIR. The discrimination capability of the classifiers was assessed for accuracy, sensitivity (pregnancy), specificity (nonpregnancy), and area under the receiver operator characteristic curve (AUC). Within all IVP fresh embryos (birth rate = 52%), high AUC were obtained at birth, especially with expanded blastocysts (CM: 0.80 +/- 0.053; plasma: 0.89 +/- 0.034). The AUC of vitrified IVP embryos (birth rate = 31%) were 0.607 +/- 0.038 (CM, expanded blastocysts) and 0.672 +/- 0.023 (plasma, all stages). Recipient plasma generally predicted pregnancy outcome better than did embryo CM. Embryos and recipients with improved pregnancy viability were identified, which could increase the economic benefit to the breeding industry.Conference Object Citation Count: 0Whole Genome Analysis Identifies Interleukin-6 Mediated Inhibition of Interferon-Induced 15 kDa Protein (ISG15), an Auto-Inflammation Suppressor Protein in Preeclamptic Cytotrophoblasts(Sage Publications inc, 2015) Tabak, Selcuk; Semerci, Nihan; Uyar, Asli; Kayisli, Ozlem Guzeloglu; Guller, Seth; Schatz, Frederick; Kayisli, Umit A.; Bilgisayar Mühendisliği / Computer Engineering[No Abstract Available]Conference Object Citation Count: 0Sampling bias in microarray data analysis: A demonstration in the field of reproductive biology(IEEE Computer Society, 2013) Manafi,S.; Uyar,A.; Bener,A.; Bilgisayar Mühendisliği / Computer EngineeringThe actual benefit from high-throughput microarray experiments strongly relies on elimination of all possible sources of biases during both the experimental procedure and data analysis process. Within the context of reproductive biology, microarray based transcriptomic analysis of oocyte and surrounding cumulus/granulosa cells poses significant challenges due to limited amount of samples and/or potential contaminations from adjacent cells. In this study, we investigated the effect of sampling bias on consistency of the microarray differential expression analysis in the field of reproduction. Experiments were conducted on five datasets obtained from publicly available microarray repositories. For each dataset, probe level expression values were extracted and background adjustment, inter-array quantile normalization and probe set summarization were performed according to the Robust Multi-Chip Average algorithm. Genes with a false discovery rate-corrected p value of <0.05 and |Fold Change| > 2 were considered as differentially expressed. Results demonstrate that both number of replicates and including different subsets of available samples in the analysis alter the number of differentially expressed genes. We suggest that assessment of inter-sample variance prior to differential expression analysis is an important step in microarray experiments and proper handling of that variance may require alternative normalization and/or statistical test methods. © 2013 IEEE.Article Citation Count: 1Yapay Zeka Tabanlı Klinik Karar Destek Sistemi ile Tüp Bebek Tedavisi Gebelik Sonucu Tahmini(2021) Pacci, Zeynep; Attar, Rukset; Şengül, Yasemin Atılgan; Alagöz, Oya; Uyar, Aslı; Bilgisayar Mühendisliği / Computer EngineeringTüp bebek tedavisi başarı olasılığının henüz tedavi başlamadan belirlenmesi hastalar ve klinisyenler açısından önem taşımaktadır. Yapay zeka tabanlı klinik karar destek sistemleri, geçmiş tedavi verilerini analiz ederek yeni tedavilerde gebelik sonucunun tahmin edilmesine olanak sağlar. Bu çalışmada, tüp bebek tedavisine başlayacak hastaya ait öznitelikler kullanılarak pozitif gebelik olasılığını hesaplayan bir model geliştirilmiştir. Çalışmada kullanılan veri kümesi Yeditepe Üniversitesi Hastanesi Tüp Bebek Kliniği’nde 2013-2019 yılları arasında gerçekleştirilen 1154 adet tedavi siklusuna ait elektronik sağlık kayıtlarından oluşmaktadır. Veri kümesi üzerinde beş farklı sınıflandırma yöntemi (Destek Vektör Makineleri, Çok Katmanlı Algılayıcı, Rastgele Orman, Aşırı Gradyan Artırma ve Hafif Gradyan Artırma) 5-katlı çapraz doğrulama yöntemi kullanılarak karşılaştırmalı olarak incelenmiştir. Gebelik sonucu tahmininde en yüksek sınıflandırma performansı Destek Vektör Makineleri yöntemi ile elde edilmiş (AUC=0.70) ve sınıflandırma olasılık sonuçlarında karar eşik değerinin optimizasyonu ile tahmin doğruluğu daha da iyileştirilerek gebelik sonucunun %71.7 Doğru Pozitif ve %59.4 Doğru Negatif oranı ile tahmin edilmesi sağlanmıştır.Article Citation Count: 27Metabolomic Prediction of Pregnancy Viability in Superovulated Cattle Embryos and Recipients with Fourier Transform Infrared Spectroscopy(Hindawi Ltd, 2014) Munoz, Marta; Uyar, Asli; Correia, Eva; Ponsart, Claire; Guyader-Joly, Catherine; Martinez-Bello, Daniel; Gomez, Enrique; Bilgisayar Mühendisliği / Computer EngineeringWe analyzed embryo culture medium (CM) and recipient blood plasma using Fourier transform infrared spectroscopy (FTIR) metabolomics to identify spectral models predictive of pregnancy outcome. Embryos collected on Day 6 from superovulated cows in 2 countries were individually cultured in synthetic oviduct fluid medium with BSA for 24 h before embryo transfer. Spent CM, blank controls, and plasma samples (Day 0 and Day 7) were evaluated using FTIR. The spectra obtained were analyzed. The discrimination capability of the classifiers was assessed for accuracy, sensitivity (pregnancy), specificity (nonpregnancy), and area under the ROC curve (AUC). Endpoints considered were Day 60 pregnancy and birth. High AUC was obtained for Day 60 pregnancy in CM within individual laboratories (France AUC = 0.751 +/- 0.039, Spain AUC = 0.718 +/- 0.024), while cumulative data decreased the AUC (AUC = 0.604 +/- 0.029). Predictions for CM at birth were lower than Day 60 pregnancy. Predictions with plasma at birth improved cumulative over individual results (Day 0: France AUC = 0.690 +/- 0.044; Spain AUC < 0.55; cumulative AUC = 0.747 +/- 0.032). Plasma generally predicted pregnancy and birth better than CM. These first results show that FTIR metabolomics could allow the identification of embryos and recipients with improved pregnancy viability, which may contribute to increasing the efficiency of selection schemes based on ET.Conference Object Citation Count: 0PERFORMANCE ANALYSIS OF CLASSIFICATION MODELS FOR MEDICAL DIAGNOSTIC DECISION SUPPORT SYSTEMS(Ieee, 2013) Segmen, Esref; Uyar, Asli; Bilgisayar Mühendisliği / Computer EngineeringAs a part of electronic healthcare systems, medical diagnostic decision support systems have been more popular in clinical routine. It is critical to decide the best model to provide reliable machine learning based decision support in diagnostic problems. In this study, the performance of common classification algorithms have been comparatively evaluated using public medical datasets. The experimental results reveal that, although there is no single best algorithm for all datasets, MLP and Naive Bayes methods have provided relatively higher success rates.
