PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Citation - WoS: 26Citation - Scopus: 31miRcorrNet: Machine Learning-Based Integration of miRNA and mRNA Expression Profiles, Combined with Feature Grouping and Ranking(PeerJ Inc., 2021-05-19) Yousef, M.; Göy, G.; Mitra, R.; Eischen, C.M.; Jabeer, A.; Bakir-Güngör, B.A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high throughput technologies allowed to generate mRNA and microRNA (miRNA) expression profiles; and the integrative analysis of these profiles allowed to uncover the functional effects of RNA expression in complex diseases, such as cancer. Several researches attempt to integrate miRNA and mRNA expression profiles using statistical methods such as Pearson correlation, and then combine it with enrichment analysis. In this study, we developed a novel tool called miRcorrNet, which performs machine learning-based integration to analyze miRNA and mRNA gene expression profiles. miRcorrNet groups mRNAs based on their correlation to miRNA expression levels and hence it generates groups of target genes associated with each miRNA. Then, these groups are subject to a rank function for classification. We have evaluated our tool using miRNA and mRNA expression profiling data downloaded from The Cancer Genome Atlas (TCGA), and performed comparative evaluation with existing tools. In our experiments we show that miRcorrNet performs as good as other tools in terms of accuracy (reaching more than 95% AUC value). Additionally, miRcorrNet includes ranking steps to separate two classes, namely case and control, which is not available in other tools. We have also evaluated the performance of miRcorrNet using a completely independent dataset. Moreover, we conducted a comprehensive literature search to explore the biological functions of the identified miRNAs. We have validated our significantly identified miRNA groups against known databases, which yielded about 90% accuracy. Our results suggest that miRcorrNet is able to accurately prioritize pan-cancer regulating high-confidence miRNAs. miRcorrNet tool and all other supplementary files are available at https://github.com/ malikyousef/miRcorrNet. © 2021 Elsevier B.V., All rights reserved.Article Topological Feature Generation for Link Prediction in Biological Networks(PeerJ Inc, 2023-05-09) Temiz, Mustafa; Bakir-Gungor, Burcu; Sahan, Pinar Guner; Coskun, Mustafa; Güner Şahan, PınarGraph or network embedding is a powerful method for extracting missing or potential information from interactions between nodes in biological networks. Graph embedding methods learn representations of nodes and interactions in a graph with low-dimensional vectors, which facilitates research to predict potential interactions in networks. However, most graph embedding methods suffer from high computational costs in the form of high computational complexity of the embedding methods and learning times of the classifier, as well as the high dimensionality of complex biological networks. To address these challenges, in this study, we use the Chopper algorithm as an alternative approach to graph embedding, which accelerates the iterative processes and thus reduces the running time of the iterative algorithms for three different (nervous system, blood, heart) undirected protein-protein interaction (PPI) networks. Due to the high dimensionality of the matrix obtained after the embedding process, the data are transformed into a smaller representation by applying feature regularization techniques. We evaluated the performance of the proposed method by comparing it with state-of-the-art methods. Extensive experiments demonstrate that the proposed approach reduces the learning time of the classifier and performs better in link prediction. We have also shown that the proposed embedding method is faster than state-of-the-art methods on three different PPI datasets.Article Theoretical Investigation of Steric Effects on the S1 Potential Energy Surface of O-Carborane Derivatives(Tubitak Scientific & Technological Research Council Turkey, 2023-01-01) Alkan, FahriTDDFT scan calculations were performed for s-carborane-anthracene derivatives (o-CB-X-Ant where X=-H,-CH3,-C2H5 and tert-butyl or-tBu) in order to understand the interplay between the steric effects, S1 potential energy surface (PES) and photophysical properties. The results show that all systems exhibit three local minima on the S1 PES, which correspond to the emissive LE and TICT state, along with the nonemissive CT state respectively. In the case of the unsubstituted system (o-CB-H-Ant), and-CH3 and-C2H5 substituted cases, S1 PES is predicted to be quite flat for certain conformations indicating that it is possible for these systems to reach the nonemissive CT state without a large energy penalty. In comparison, conformational pathways for the nonemissive CT state are predicted to be energetically unfavorable for o-CB-tBu-Ant as a result of both steric and electronic effects. These results provide a mechanism for the enhanced emission of cr-CB-fluorophore molecules with bulky ligands.Article Citation - WoS: 3Citation - Scopus: 3Theoretical Investigation of Substituent Effects on the Relative Stabilities and Electronic Structure of [BnXn]2- Clusters(Springer, 2021-11-29) Tahaoglu, Duygu; Alkan, Fahri; Durandurdu, MuratIn this study, we provide a theoretical evaluation of relative stabilities and electronic structure for [BnXn](2-) clusters (n = 10, 12, 13, 14, 15, 16). Structural and electronic characteristics of [BnXn](2-) clusters are examined by comparison with the [B12X12](2-) counterparts with a focus on the substituent effects (X = H, F, Cl, Br, CN, BO, OH, NH2) on the electronic structure, electron detachment energies, formation enthalpies, and charge distributions. For the electronic structure and electron detachment energies, substituent effects on boron clusters are shown to follow a very similar trend to the mesomeric and inductive effects (+/- M and +/- I) of pi-conjugated systems, and the most stable derivatives in terms of HOMO/LUMO and electron detachment energies are calculated for CN and BO substituents due to strong -M effects. In the case of formation enthalpies for larger boron clusters (n >= 13), the icosahedral barrier is shown to increase with the halogen and CN substitution, whereas it is possible to reduce the icosahedral barrier for the cases of X = OH and NH2. It is shown that this reduction results from destabilizing the [B12X12](2-) cluster with electronic (+ M) and symmetry effects induced by OH and NH2 ligands.Article Citation - WoS: 43Citation - Scopus: 49The Pleiotropic Effects of Fisetin and Hesperetin on Human Acute Promyelocytic Leukemia Cells Are Mediated Through Apoptosis, Cell Cycle Arrest, and Alterations in Signaling Networks(Sage Publications Ltd, 2015-06-17) Adan, Aysun; Baran, YusufFisetin and hesperetin, flavonoids from various plants, have several pharmaceutical activities including antioxidative, anti-inflammatory, and anticancer effects. However, studies elucidating the role and the mechanism(s) of action of fisetin and hesperetin in acute promyelocytic leukemia are absent. In this study, we investigated the mechanism of the antiproliferative and apoptotic actions exerted by fisetin and hesperetin on human HL60 acute promyelocytic leukemia cells. The viability of HL60 cells was evaluated using the MTT assay, apoptosis by annexin V/propidium iodide (PI) staining and cell cycle distribution using flow cytometry, and changes in caspase-3 enzyme activity and mitochondrial transmembrane potential. Moreover, we performed whole-genome microarray gene expression analysis to reveal genes affected by fisetin and hesperetin that can be important for developing of future targeted therapy. Based on data obtained from microarray analysis, we also described biological networks modulated after fisetin and hesperetin treatment by KEGG and IPA analysis. Fisetin and hesperetin treatment showed a concentration- and time-dependent inhibition of proliferation and induced G2/M arrest for both agents and G0/G1 arrest for hesperetin at only the highest concentrations. There was a disruption of mitochondrial membrane potential together with increased caspase-3 activity. Furthermore, fisetin- and hesperetin-triggered apoptosis was confirmed by annexin V/PI analysis. The microarray gene profiling analysis revealed some important biological pathways including mitogen-activated protein kinases (MAPK) and inhibitor of DNA binding (ID) signaling pathways altered by fisetin and hesperetin treatment as well as gave a list of genes modulated a parts per thousand yen2-fold involved in cell proliferation, cell division, and apoptosis. Altogether, data suggested that fisetin and hesperetin have anticancer properties and deserve further investigation.Article Citation - WoS: 1Citation - Scopus: 1The Impact of COVID-19 on Healthcare Utilization in Turkey(Elsevier, 2024-09) Ugur, Zeynep B.; Durak, AysenurObjectives: This study investigates the impact of the COVID-19 pandemic on healthcare utilization in Turkey. Methods: We utilized individual-level data derived from Turkish Statistical Institute 's annual surveys between 2014 and 2022 and estimated probit regression models. Results: We find that COVID-19 pandemic reduced healthcare utilization by 11.8% after taking into account a large set of background variables. Although our study finds that the elderly and those with health problems are more likely to use healthcare services under normal circumstances, the COVID-19 pandemic has caused notable drops in the healthcare utilization among the elderly (-6.5%) and those with health problems (-3.8%). Although those without health insurance had lower utilization of healthcare services before the pandemic, during the pandemic they were not particularly hit. Conclusion: We conclude that the pandemic did not lower the healthcare utilization in Turkey because of the supply constraints. Also, the evidence points to the reduced demand due to the fear of contagion rather than financial concerns.Article Citation - WoS: 15Citation - Scopus: 11T Cells in Tumor Microenvironment(Springer, 2015-10-18) Kiraz, Yagmur; Baran, Yusuf; Nalbant, AytenTumors progress in a specific area, which supports its development, spreading or shrinking in time with the presence of different factors that effect the fate of the cancer cells. This specialized site is called "tumor microenvironment" and has a composition of heterogenous materials. The immune cells are also residents of this stromal, cancerous, and inflammatory environment, and their types, densities, or functional differences are one of the key factors that mediate the fate of a tumor. T cells as a vital part of the immune system also are a component of tumor microenvironment, and their roles have been elucidated in many studies. In this review, we focused on the immune system components by focusing on T cells and detailed T helper cell subsets in tumor microenvironment and how their behaviors affect either the tumor or the patient's outcome.Article Citation - WoS: 48Citation - Scopus: 65Review of Feature Selection Approaches Based on Grouping of Features(PeerJ Inc, 2023-07-17) Kuzudisli, Cihan; Bakir-Gungor, Burcu; Bulut, Nurten; Qaqish, Bahjat; Yousef, MalikWith the rapid development in technology, large amounts of high-dimensional data have been generated. This high dimensionality including redundancy and irrelevancy poses a great challenge in data analysis and decision making. Feature selection (FS) is an effective way to reduce dimensionality by eliminating redundant and irrelevant data. Most traditional FS approaches score and rank each feature individually; and then perform FS either by eliminating lower ranked features or by retaining highly -ranked features. In this review, we discuss an emerging approach to FS that is based on initially grouping features, then scoring groups of features rather than scoring individual features. Despite the presence of reviews on clustering and FS algorithms, to the best of our knowledge, this is the first review focusing on FS techniques based on grouping. The typical idea behind FS through grouping is to generate groups of similar features with dissimilarity between groups, then select representative features from each cluster. Approaches under supervised, unsupervised, semi supervised and integrative frameworks are explored. The comparison of experimental results indicates the effectiveness of sequential, optimization-based (i.e., fuzzy or evolutionary), hybrid and multi-method approaches. When it comes to biological data, the involvement of external biological sources can improve analysis results. We hope this work's findings can guide effective design of new FS approaches using feature grouping.Article Citation - WoS: 29Citation - Scopus: 30Revealing Genome-Wide mRNA and MicroRNA Expression Patterns in Leukemic Cells Highlighted HSA-MIR as a Tumor Suppressor for Regain of Chemotherapeutic Imatinib Response due to Targeting STAT5A(Sage Publications Ltd, 2015-05-08) Kaymaz, Burcin Tezcanli; Gunel, Nur Selvi; Ceyhan, Metin; Cetintas, Vildan Bozok; Ozel, Buket; Yandim, Melis Kartal; Can, Buket KosovaBCR-ABL oncoprotein stimulates cell proliferation and inhibits apoptosis in chronic myeloid leukemia (CML). For cure, imatinib is a widely used tyrosine kinase inhibitor, but developing chemotherapeutic resistance has to be overcome. In this study, we aimed to determine differing genome-wide MicroRNA (miRNA) and messenger RNA (mRNA) expression profiles in imatinib resistant (K562/IMA-3 mu M) and parental cells by targeting STAT5A via small interfering RNA (siRNA) applications. After determining possible therapeutic miRNAs, we aimed to check their effects upon cell viability and proliferation, apoptosis, and find a possible miRNAArticle Citation - WoS: 18Citation - Scopus: 20Resveratrol Triggers Anti-Proliferative and Apoptotic Effects in FLT3-LTD Acute Myeloid Leukemia Cells via Inhibiting Ceramide Catabolism Enzymes(Humana Press inc, 2022-01-20) Ersoz, Nur Sebnem; Adan, AysunResveratrol possesses well-defined anti-carcinogenic activities. However, how resveratrol exerts its anti-leukemic actions by modulating anti-apoptotic ceramide catabolism enzymes, mainly sphingosine kinase (SK-1) and glucosylceramide synthase (GCS), in FLT3-ITD AML remains unclear. Resveratrol, SKI II (SK inhibitor) and PDMP (GCS inhibitor) were evaluated alone or in combinations for their effect on cell proliferation (MTT assay), apoptosis (annexin V-FITC/PI staining by flow cytometry) and cell cycle progression (PI staining by flow cytometry) in MOLM-13 and MV4-11 cells. The combination indexes (CIs) were calculated based on cell proliferation data using CompuSyn software. Caspase-3 and PARP activation, changes in SK-1 and GCS levels by resveratrol alone or PARP cleavage in co-treatments were determined by western blot. Resveratrol and inhibitors alone inhibited cell proliferation in a dose- and time-dependent manner. Resveratrol downregulated SK-1 and GCS expression in both cell lines. It induced apoptosis by phosphatidylserine (PS) exposure together with caspase-3 and PARP cleavage and arrested the cell cycle slightly at the S phase. Co-administrations intensified resveratrol's effect by inhibiting cell proliferation synergistically (A CI of < 1) or additively (A CI 1.0-1.1) and inducing apoptosis via PS relocalization and PARP cleavage. Resveratrol plus SKI II did not affect cell cycle progression significantly, however, resveratrol plus PDMP blocked cycle progression at G0/G1 and S phases for MOLM-13 cells and MV4-11 cells, respectively. Overall, resveratrol may inhibit FLT3-ITD AML cell proliferation by inhibiting ceramide catabolism and be evaluated as a chemopreventive after detailed analysis of the crosstalk between resveratrol and ceramide catabolism pathway.