WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 38Citation - Scopus: 38pH- and Temperature-Responsive Amphiphilic Diblock Copolymers of 4-Vinylpyridine and Oligoethyleneglycol Methacrylate Synthesized by RAFT Polymerization(Elsevier Sci Ltd, 2014-01) Topuzogullari, Murat; Bulmus, Volga; Dalgakiran, Eray; Dincer, SevilDiblock copolymers of 4-vinylpyridine (4VP) and oligoethyleneglycol methyl ether methacrylate (OEGMA) were synthesized for the first time using RAFT polymerization technique as potential drug delivery systems. Effects of the number of ethylene glycol units in OEGMA, chain length of hydrophobic P4VP block, pH, concentration and temperature on the solution behavior of the copolymers were investigated comprehensively. Copolymer chains formed micelles at pH values higher than 5 whereas unimeric polymers were observed to exist below pH 5, owing to the repulsion between positively charged P4VP blocks. The size of the micelles was dependent on the relative length of blocks, P4VP and POEGMA. Thermo-responsive properties of copolymers were investigated depending on the pH and length of P4VP block. The increase in the length of P4VP block decreased the LCST substantially at pH 7. At pH 3, LCST of copolymers shifted to higher temperatures due to the increased interaction of copolymers with water through positively charged P4VP block. (C) 2013 Elsevier Ltd. All rights reserved.Article Citation - WoS: 26Citation - Scopus: 33miRmoduleNet: Detecting miRNA-mRNA Regulatory Modules(Frontiers Media S.A., 2022-04-12) Yousef, Malik; Goy, Gokhan; Bakir-Gungor, BurcuIncreasing evidence that MicroRNAs (miRNAs) play a key role in carcinogenesis has revealed the need for elucidating the mechanisms of miRNA regulation and the roles of miRNAs in gene-regulatory networks. A better understanding of the interactions between miRNAs and their mRNA targets will provide a better understanding of the complex biological processes that occur during carcinogenesis. Increased efforts to reveal these interactions have led to the development of a variety of tools to detect and understand these interactions. We have recently described a machine learning approach miRcorrNet, based on grouping and scoring (ranking) groups of genes, where each group is associated with a miRNA and the group members are genes with expression patterns that are correlated with this specific miRNA. The miRcorrNet tool requires two types of -omics data, miRNA and mRNA expression profiles, as an input file. In this study we describe miRModuleNet, which groups mRNA (genes) that are correlated with each miRNA to form a star shape, which we identify as a miRNA-mRNA regulatory module. A scoring procedure is then applied to each module to further assess their contribution in terms of classification. An important output of miRModuleNet is that it provides a hierarchical list of significant miRNA-mRNA regulatory modules. miRModuleNet was further validated on external datasets for their disease associations, and functional enrichment analysis was also performed. The application of miRModuleNet aids the identification of functional relationships between significant biomarkers and reveals essential pathways involved in cancer pathogenesis.Article Citation - WoS: 20Citation - Scopus: 24miRdisNET: Discovering MicroRNA Biomarkers That Are Associated With Diseases Utilizing Biological Knowledge-Based Machine Learning(Frontiers Media S.A., 2023-01-12) Jabeer, Amhar; Temiz, Mustafa; Bakir-Gungor, Burcu; Yousef, MalikDuring recent years, biological experiments and increasing evidence have shown that MicroRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex diseases, it is necessary to reveal the associations between a specific disease and related miRNAs. Although current computational models based on machine learning attempt to determine miRNA-disease associations, the accuracy of these models need to be improved, and candidate miRNA-disease relations need to be evaluated from a biological perspective. In this paper, we propose a computational model named miRdisNET to predict potential miRNA-disease associations. Specifically, miRdisNET requires two types of data, i.e., miRNA expression profiles and known disease-miRNA associations as input files. First, we generate subsets of specific diseases by applying the grouping component. These subsets contain miRNA expressions with class labels associated with each specific disease. Then, we assign an importance score to each group by using a machine learning method for classification. Finally, we apply a modeling component and obtain outputs. One of the most important outputs of miRdisNET is the performance of miRNA-disease prediction. Compared with the existing methods, miRdisNET obtained the highest AUC value of .9998. Another output of miRdisNET is a list of significant miRNAs for disease under study. The miRNAs identified by miRdisNET are validated via referring to the gold-standard databases which hold information on experimentally verified MicroRNA-disease associations. miRdisNET has been developed to predict candidate miRNAs for new diseases, where miRNA-disease relation is not yet known. In addition, miRdisNET presents candidate disease-disease associations based on shared miRNA knowledge. The miRdisNET tool and other supplementary files are publicly available at: .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 Citation - WoS: 5Workplace Diversity and Intercultural Communication: A Phenomenological Study(Taylor & Francis As, 2017-01-01) Evans, Adam; Suklun, HarikaFor decades, the United States has seen an increasing number of immigrants, which has led to a significant increase in cultural diversity in the United States. This phenomenological study examines the contextual history of professional non-native English-speaking women in the United States to form a basis of comparison with native English speakers. It attempts to compare their lived communicative experiences with those of non-native English speakers in the workplace. In this study, 16 professional, native English-speaking women currently working in the US were interviewed. Participants in this study were asked to describe professional and intercultural experiences through interactions with non-native English-speaking coworkers, any expectations of the interactions or violations of those expectations, and any miscommunications that may have occurred. Many native English speakers positively reflected upon these intercultural interactions and shared examples of their vocal adjustments and challenges of verbal and intercultural communication. To overcome these challenges, professional native English speakers described trying to slow speech or asking confirming questions such as Do you understand? to mitigate verbal conflicts and miscommunication. Based on the trends within the responses, however, there is a potential for unintentional and often offensive consequences to occur. Several coping mechanisms were found to be considered rude or off-putting by non-native speakers, while the intent of a more direct message was often misinterpreted by native English speakers. In addition, it seems that native English speakers often may have good intentions in their actions but do not have the skillset to better facilitate communication with non-native English speakers.Article Citation - WoS: 24Citation - Scopus: 26Wireless Measurement of Elastic and Plastic Deformation by a Metamaterial-Based Sensor(MDPI, 2014-10-20) Ozbey, Burak; Demir, Hilmi Volkan; Kurc, Ozgur; Erturk, Vakur B.; Altintas, AyhanWe report remote strain and displacement measurement during elastic and plastic deformation using a metamaterial-based wireless and passive sensor. The sensor is made of a comb-like nested split ring resonator (NSRR) probe operating in the near-field of an antenna, which functions as both the transmitter and the receiver. The NSRR probe is fixed on a standard steel reinforcing bar (rebar), and its frequency response is monitored telemetrically by a network analyzer connected to the antenna across the whole stress-strain curve. This wireless measurement includes both the elastic and plastic region deformation together for the first time, where wired technologies, like strain gauges, typically fail to capture. The experiments are further repeated in the presence of a concrete block between the antenna and the probe, and it is shown that the sensing system is capable of functioning through the concrete. The comparison of the wireless sensor measurement with those undertaken using strain gauges and extensometers reveals that the sensor is able to measure both the average strain and the relative displacement on the rebar as a result of the applied force in a considerably accurate way. The performance of the sensor is tested for different types of misalignments that can possibly occur due to the acting force. These results indicate that the metamaterial-based sensor holds great promise for its accurate, robust and wireless measurement of the elastic and plastic deformation of a rebar, providing beneficial information for remote structural health monitoring and post-earthquake damage assessment.Article Citation - WoS: 29Citation - Scopus: 32Wind Farm Site Selection Using GIS-Based Multicriteria Analysis With Life Cycle Assessment Integration(Springer Heidelberg, 2024-01-19) Demir, Abdullah; Dincer, Ali Ersin; Ciftci, Cihan; Gulcimen, Sedat; Uzal, Nigmet; Yilmaz, KutayThe sustainability of wind power plants depends on the selection of suitable installation locations, which should consider not only economic and technical factors including manufacturing and raw materials, but also issues pertaining to the environment. In the present study, a novel methodology is proposed to determine the suitable locations for wind turbine farms by analyzing from the environmental perspective. In the methodology, the life cycle assessment (LCA) of wind turbines is incorporated into the decision process. The criteria are ranked using analytical hierarchy process (AHP). The study area is chosen as the western region of Turkiye. The obtained suitability map reveals that wind speed is not the sole criterion for selecting a site for wind turbine farms; other factors, such as bird migration paths, distance from urban areas and land use, are also crucial. The results also reveal that constructing wind power plants in the vicinity of Izmir, canakkale, Istanbul, and Balikesir in Turkiye can lead to a reduction in emissions. Izmir and its surrounding area show the best environmental performance with the lowest CO2 per kilowatt-hour (7.14 g CO2 eq/kWh), to install a wind turbine due to its proximity to the harbor and steel factory across the study area. canakkale and the northwest region of Turkiye, despite having high wind speeds, are less environmentally favorable than Izmir, Balikesir, and Istanbul. The findings of LCA reveal that the nacelle and rotor components of the wind turbine contribute significantly (43-97%) to the environmental impact categories studied, while the tower component (0-36%) also has an impact.Article Citation - WoS: 1Citation - Scopus: 1Why Are Faculty Unfavorably Disposed to MOOCs? – A Sharing of Views by Chinese Hospitality Educators(Routledge Journals, Taylor & Francis Ltd, 2021-08-12) Zhang, Xin; Koseoglu, Mehmet Ali; King, Brian; Aladag, Omer FarukThis study explores the negative disposition of many hospitality higher education faculty toward MOOCs, an increasingly prominent delivery mode in pedagogical discourse which potentially enriches student learning. Such enrichment is particularly welcome in the case of hospitality because of its diverse stakeholders and student learning needs. The researchers conducted an in-depth and qualitative exploration with faculty members in mainland China. They combined the Diffusion of Innovation (DOI) approach and theory of motivation to propose five dimensions that account for groupings of resistance to deploying MOOCs. These are attributes and complexities, perceived incompatibility, unsuitability for trial, and lack of observational capacity. The study contributes to knowledge by examining the perspectives of faculty who have the capacity to constrain the deployment of MOOCs. The authors suggest that faculty members should be encouraged to embrace MOOCs as an innovative medium for learning and teaching.Article Citation - WoS: 6Citation - Scopus: 6WDR31 Displays Functional Redundancy With GTpase-Activating Proteins (GAPs) ELMOD and RP2 in Regulating Ift Complex and Recruiting the BBsome to Cilium(Life Science Alliance Llc, 2023-05-19) Cevik, Sebiha; Peng, Xiaoyu; Beyer, Tina; Pir, Mustafa S.; Yenisert, Ferhan; Woerz, Franziska; Kaplan, Oktay, IThe correct intraflagellar transport (IFT) assembly at the ciliary base and the IFT turnaround at the ciliary tip are key for the IFT to perform its function, but we still have poor understanding about how these processes are regulated. Here, we identify WDR31 as a new ciliary protein, and analysis from zebrafish and Caeno-rhabditis elegans reveals the role of WDR31 in regulating the cilia morphology. We find that loss of WDR-31 together with RP-2 and ELMD-1 (the sole ortholog ELMOD1-3) results in ciliary accumu-lations of IFT Complex B components and KIF17 kinesin, with fewer IFT/BBSome particles traveling along cilia in both anterograde and retrograde directions, suggesting that the IFT/BBSome entry into the cilia and exit from the cilia are impacted. Furthermore, anterograde IFT in the middle segment travels at increased speed in wdr-31;rpi-2;elmd-1. Remarkably, a non-ciliary protein leaks into the cilia of wdr-31;rpi-2;elmd-1, possibly because of IFT de-fects. This work reveals WDR31-RP-2-ELMD-1 as IFT and BBSome trafficking regulators.Article Citation - WoS: 25Citation - Scopus: 33Volume Fraction, Thickness, and Permeability of the Sealing Layer in Microbial Self-Healing Concrete Containing Biogranules(Frontiers Media S.A., 2018-11-23) Ersan, Yusuf Cagatay; Palin, Damian; Tasdemir, Sena Busra Yengec; Tasdemir, Kasim; Jonkers, Henk M.; Boon, Nico; De Belie, Nele; Yengec Tasdemir, Sena BusraAutonomous repair systems in construction materials have become a promising alternative to current unsustainable and labor-intensive maintenance methods. Biomineralization is a popular route that has been applied to enhance the self-healing capacity of concrete. Various axenic microbial cultures were coupled with protective carriers, and their combination appears to be useful for the development of healing agents for realizing self-healing concrete. The advantageous traits of non-axenic cultures, such as economic feasibility, self-protection, and high specific activity have been neglected so far, and thus the number of studies investigating their performance as healing agents is scarce. Here we present the self-healing performance of a mortar containing a healing agent consisting of non-axenic biogranules with a denitrifying core. Mortar specimens with a defined crack width of 400 mu m were used in the experiments and treated with tap water for 28 days. Self-healing was quantified in terms of the crack volume reduction, the thickness of the sealing layer along the crack depth and water permeability under 0.1 bar pressure. Complete visual crack closure was achieved in the bio-based specimens in 28 days, the thickness of the calcite layer was recorded as 10 mm and the healed crack volume was detected as 6%. Upon self-sealing of the specimens, the water permeability decreased by 83%. Overall, non-axenic biogranules with a denitrifying core shows great potential for development of self-healing bioconcrete.