Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Article Citation - WoS: 4Citation - Scopus: 4Integrative Biological Network Analysis To Identify Shared Genes in Metabolic Disorders(Institute of Electrical and Electronics Engineers, 2022) Tenekeci, Samet; Işık, ZerrinIdentification of common molecular mechanisms in interrelated diseases is essential for better prognoses and targeted therapies. However, complexity of metabolic pathways makes it difficult to discover common disease genes underlying metabolic disorders; and it requires more sophisticated bioinformatics models that combine different types of biological data and computational methods. Accordingly, we built an integrative network analysis model to identify shared disease genes in metabolic syndrome (MS), type 2 diabetes (T2D), and coronary artery disease (CAD). We constructed weighted gene co-expression networks by combining gene expression, protein-protein interaction, and gene ontology data from multiple sources. For 90 different configurations of disease networks, we detected the significant modules by using MCL, SPICi, and Linkcomm graph clustering algorithms. We also performed a comparative evaluation on disease modules to determine the best method providing the highest biological validity. By overlapping the disease modules, we identified 22 shared genes for MS-CAD and T2D-CAD. Moreover, 19 out of these genes were directly or indirectly associated with relevant diseases in the previous medical studies. This study does not only demonstrate the performance of different biological data sources and computational methods in disease-gene discovery, but also offers potential insights into common genetic mechanisms of the metabolic disorders.Article Citation - WoS: 6Citation - Scopus: 10Efficient Privacy-Preserving Whole-Genome Variant Queries(Oxford University Press, 2022) Akgün, Mete; Pfeifer, Nico; Kohlbacher, OliverMotivation: Diagnosis and treatment decisions on genomic data have become widespread as the cost of genome sequencing decreases gradually. In this context, disease-gene association studies are of great importance. However, genomic data are very sensitive when compared to other data types and contains information about individuals and their relatives. Many studies have shown that this information can be obtained from the query-response pairs on genomic databases. In this work, we propose a method that uses secure multi-party computation to query genomic databases in a privacy-protected manner. The proposed solution privately outsources genomic data from arbitrarily many sources to the two non-colluding proxies and allows genomic databases to be safely stored in semi-honest cloud environments. It provides data privacy, query privacy and output privacy by using XOR-based sharing and unlike previous solutions, it allows queries to run efficiently on hundreds of thousands of genomic data. Results: We measure the performance of our solution with parameters similar to real-world applications. It is possible to query a genomic database with 3 000 000 variants with five genomic query predicates under 400 ms. Querying 1 048 576 genomes, each containing 1 000 000 variants, for the presence of five different query variants can be achieved approximately in 6 min with a small amount of dedicated hardware and connectivity. These execution times are in the right range to enable real-world applications in medical research and healthcare. Unlike previous studies, it is possible to query multiple databases with response times fast enough for practical application. To the best of our knowledge, this is the first solution that provides this performance for querying large-scale genomic data.Article Citation - WoS: 17Citation - Scopus: 19Pixelated Colorimetric Nucleic Acid Assay(Elsevier, 2020) Aydın, Hakan Berk; Cheema, Jamal Ahmed; Arnmanath, Gopal; Toklucu, Cihan; Yücel, Müge; Özenler, Sezer; Yıldız, Ümit HakanConjugated polyelectrolytes (CPEs) have been widely used as reporters in colorimetric assays targeting nucleic acids. CPEs provide naked eye detection possibility by their superior optical properties however, as concentration of target analytes decrease, trace amounts of nucleic acid typically yield colorimetric responses that are not readily perceivable by naked eye. Herein, we report a pixelated analysis approach for correlating colorimetric responses of CPE with nucleic acid concentrations down to 1 nM, in plasma samples, utilizing a smart phone with an algorithm that can perform analytical testing and data processing. The detection strategy employed relies on conformational transitions between single stranded nucleic acid-cationic CPE duplexes and double stranded nucleic acid-CPE triplexes that yield distinct colorimetric responses for enabling naked eye detection of nucleic acids. Cationic poly[N,N,N-triethyl-3-((4-methylthiophen-3-yl)oxy)propan-1-aminium bromide] is utilized as the CPE reporter deposited on a polyvinylidene fluoride (PVDF) membrane for nucleic acid assay. A smart phone application is developed to capture and digitize the colorimetric response of the individual pixels of the digital images of CPE on the PVDF membrane, followed by an analysis using the algorithm. The proposed pixelated approach enables precise quantification of nucleic acid assay concentrations, thereby eliminating the margin of error involved in conventional methodologies adopted for interpretation of colorimetric responses, for instance, RGB analysis. The obtained results illustrate that a ubiquitous smart phone could be utilized for point of care colorimetric nucleic acids assays in complex matrices without requiring sophisticated software or instrumentation.Article Citation - WoS: 24Citation - Scopus: 23The Effect of Age, Menopausal State, and Breast Density on 18f-Fdg Uptake in Normal Glandular Breast Tissue(Society of Nuclear Medicine and Molecular Imaging, 2010) Mavi, Ayşe; Çermik, Tevfik F.; Urhan, Muammer; Püskülcü, Halis; Basu, Sandip; Cucchiara, Andrew J.; Yu, Jian Q.; Alavi, AbassTheoretically, the degree of 18F-FDG uptake in the glandular tissues of the normal breast can affect the detection of breast cancer. The aim of this prospective study was to investigate relationships among age, menopausal state, and breast density and determine whether they affect 18F-FDG uptake in normal glandular breast tissue. Methods: Among 250 newly diagnosed breast cancer patients, 149 patients (mean age ± SD, 50.9 ± 9.70 y; range, 32-77 y) were analyzed because they had normal contralateral breasts confirmed by MRI, mammography, and 18F-FDG PET examinations. PET images were acquired 60 ± 2 min after the administration of 18F-FDG (5.2 MBq/kg of body weight). The maximum and average standardized uptake value (SUVmax and SUVavg, respectively) of 18F-FDG were calculated in the normal breast. Patients were divided into groups according to qualitative breast density and menopausal state. Descriptive statistics and 2-factorial analysis of covariance were used to assess the effects of qualitative breast density, menopausal state, and age on SUVmax and SUVavg. Pearson χ2 was used to test the relationship between menopausal state and qualitative breast density. Results: The average age of patients with nondense breasts was significantly higher than that of patients with dense breasts (P < 0.01). Also, breast density related to menopausal state (P < 0.05). Dense breasts had an average SUVmax of 1.243 and mean SUVavg of 0.694, whereas nondense breasts had a mean SUVmax of 0.997 and mean SUVavg of 0.592. Analysis of covariance indicated that density and the linear effect of age were significant with regard to both SUVmax and SUVavg. After removing the linear effect of age, menopausal state had no effect on SUVmax and SUVavg. Conclusion: 18F-FDG uptake significantly decreases as age increases and breast density decreases. Age and qualitative breast density are independent factors and significantly affect 18F-FDG uptake for both SUVmax and SUVavg. Menopausal state had no effect on SUVmax and SUVavg. Copyright © 2010 by the Society of Nuclear Medicine, Inc.Article Citation - WoS: 72Citation - Scopus: 75The Effects of Estrogen, Progesterone, and C-Erbb Receptor States on 18f-Fdg Uptake of Primary Breast Cancer Lesions(Society of Nuclear Medicine and Molecular Imaging, 2007) Mavi, Ayşe; Çermik, Tevfik F.; Urhan, Muammer; Püskülcü, Halis; Basu, Sandip; Yu, Jian Q.; Zhuang, Hongming; Czerniecki, Brian; Alavi, AbassThe purpose of this prospective study was to investigate whether correlations exist between 18F-FDG uptake of primary breast cancer lesions and predictive and prognostic factors such as estrogen receptor (ER), progesterone receptor (PR), and C-erbB-2 receptor (C-erbB-2R) states. Methods: Before undergoing partial or total mastectomy, 213 patients with newly diagnosed breast cancer underwent 18F-FDG PET (5.2 MBq/kg of body weight). The maximum standardized uptake value (SUV) of the primary lesion was measured in each patient. Standard immunohistochemistry was performed on a surgical specimen of the cancer lesion to characterize the receptor state of the tumor cells. Pearson χ2 tests were performed on the cross-tables of different receptor states to test any association that may exist among ER, PR, and C-erbB-2R. Maximum SUV measurements for different receptor states were compared using factorial ANOVA in a completely random design. Results: After exclusion of certain lesions, 118 lesions were analyzed for this study. The mean maximum SUVs of ER-positive and ER-negative lesions were 3.03 ± 0.26 and 5.64 ± 0.75, whereas those of PR were 3.24 ± 0.29 and 4.89 ± 0.67, respectively, and those of C-erbB-2R were 4.64 ± 0.70 and 3.70 ± 0.35, respectively, χ2 tests for ER and PR showed that if one is positive then the other tends to be positive as well (χ2 = 71.054, P < 0.01). For ER and C-erbB-2R states, if ER is positive, C-erbB-2R will more likely be negative (χ2 = 13.026, P < 0.01). No relationship was detected between PR and C-erbB-2R states (χ2 = 3.695, P > 0.05). ANOVAs showed that PR state alone (F = 0.095, P > 0.05) and C-erbB-2R state alone (F = 0.097, P > 0.05) had no effect on 18F-FDG uptake but ER state alone had an effect (F = 9.126, P < 0.01). ER and PR being together had no additional effect on 18F-FDG uptake. Our study also demonstrated that interactions exist between ER and C-erbB-2R state and between PR and C-erbB-2R state. Conclusion: SUV measurements may provide valuable information about the state of ER, PR, and C-erbB-2R and the associated glucose metabolism as measured by 18F-FDG uptake of the primary breast cancer lesions. Such an association may be of importance to treatment planning and outcome in these patients.