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: 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: 8Citation - Scopus: 8Writing Chemical Patterns Using Electrospun Fibers as Nanoscale Inkpots for Directed Assembly of Colloidal Nanocrystals(Royal Soc Chemistry, 2020) Kiremitler, N. Burak; Torun, Ilker; Altintas, Yemliha; Patarroyo, Javier; Demir, Hilmi Volkan; Puntes, Victor F.; Onses, M. SerdarApplications that range from electronics to biotechnology will greatly benefit from low-cost, scalable and multiplex fabrication of spatially defined arrays of colloidal inorganic nanocrystals. In this work, we present a novel additive patterning approach based on the use of electrospun nanofibers (NFs) as inkpots for end-functional polymers. The localized grafting of end-functional polymers from spatially defined nanofibers results in covalently bound chemical patterns. The main factors that determine the width of the nanopatterns are the diameter of the NF and the extent of spreading during the thermal annealing process. Lowering the surface energy of the substrates via silanization and a proper choice of the grafting conditions enable the fabrication of nanoscale patterns over centimeter length scales. The fabricated patterns of end-grafted polymers serve as the templates for spatially defined assembly of colloidal metal and metal oxide nanocrystals of varying sizes (15 to 100 nm), shapes (spherical, cube, rod), and compositions (Au, Ag, Pt, TiO2), as well as semiconductor quantum dots, including the assembly of semiconductor nanoplatelets.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: 13Citation - Scopus: 13Why Do Muse Stem Cells Present an Enduring Stress Capacity? Hints From a Comparative Proteome Analysis(MDPI, 2021-02-19) Acar, Mustafa B.; Aprile, Domenico; Ayaz-Guner, Serife; Guner, Huseyin; Tez, Coskun; Di Bernardo, Giovanni; Galderisi, UmbertoMuse cells are adult stem cells that are present in the stroma of several organs and possess an enduring capacity to cope with endogenous and exogenous genotoxic stress. In cell therapy, the peculiar biological properties of Muse cells render them a possible natural alternative to mesenchymal stromal cells (MSCs) or to in vitro-generated pluripotent stem cells (iPSCs). Indeed, some studies have proved that Muse cells can survive in adverse microenvironments, such as those present in damaged/injured tissues. We performed an evaluation of Muse cells' proteome under basic conditions and followed oxidative stress treatment in order to identify ontologies, pathways, and networks that can be related to their enduring stress capacity. We executed the same analysis on iPSCs and MSCs, as a comparison. The Muse cells are enriched in several ontologies and pathways, such as endosomal vacuolar trafficking related to stress response, ubiquitin and proteasome degradation, and reactive oxygen scavenging. In Muse cells, the protein-protein interacting network has two key nodes with a high connectivity degree and betweenness: NFKB and CRKL. The protein NFKB is an almost-ubiquitous transcription factor related to many biological processes and can also have a role in protecting cells from apoptosis during exposure to a variety of stressors. CRKL is an adaptor protein and constitutes an integral part of the stress-activated protein kinase (SAPK) pathway. The identified pathways and networks are all involved in the quality control of cell components and may explain the stress resistance of Muse cells.Article Citation - WoS: 39Citation - Scopus: 51What Are the Key Success Factors for Strategy Formulation and Implementation? Perspectives of Managers in the Hotel Industry(Elsevier Sci Ltd, 2020-08) Koseoglu, Mehmet Ali; Altin, Mehmet; Chan, Eric; Aladag, Omer FarukThis study investigates how hotel managers describe strategy and identify key success factors for its formulation and implementation. The study analyzes qualitative data collected through semi-structured interviews with property level top managers of hotels in Hong Kong. The findings show that hotel managers prioritize competition analysis and macro-environmental conditions over internal characteristics such as teamwork in strategy formulation. In the implementation phase, however, internal considerations such as employee involvement and strategic consensus are given prominence. This study provides a significant contribution by examining how top level practitioners in the industry interpret success factors in their strategic management efforts, and it highlights a largely neglected area in the hospitality and tourism management literature.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: 13Citation - Scopus: 14Unravelling the Moderating Roles of Environmental Regulations on the Impact of Foreign Direct Investment on Environmental Sustainability(Academic Press Ltd- Elsevier Science Ltd, 2025-02) Ehigiamusoe, Kizito Uyi; Chen, Danqing; Dogan, Eyup; Binsaeed, Rima H.In the era of economic globalization, China attracts significant foreign direct investment (FDI) to accelerate economic prosperity. FDI inflows could have ramifications on environmental degradation (ED) despite the enactment of different environmental regulations (ERs) such as market-incentive, command-and-control as well as informal regulations. Though some studies have shown that FDI and ED have significant relationship, the moderating roles of different ERs on the environmental impact of FDI has not been empirically unraveled. This study fills this research gap by analyzing the direct impact of FDI on ED (i.e., carbon dioxide emissions, ecological footprint) using the provincial panel data. Second, it unravels the moderating roles of different ERs on the environmental impact of FDI in the provinces and regions. The results indicate that FDI directly mitigates ED, verifying the pollution halo hypothesis while ERs directly alleviate ED in China. However, the interaction between FDI and ERs do not alleviate ED in China albeit regional heterogeneity exist. The economic implication is that FDI is not a channel through which ERs enhance environmental sustainability in China. This study recommends some policy options arising from the findings.Article Citation - WoS: 15Citation - Scopus: 14Understanding Plasmon Coupling in Nanoparticle Dimers Using Molecular Orbitals and Configuration Interaction(Royal Soc Chemistry, 2019) Alkan, Fahri; Aikens, Christine M.We perform a theoretical investigation of the electronic structure and optical properties of atomic nanowire and nanorod dimers using DFT and TDDFT. In both systems at separation distances larger than 0.75 nm, optical spectra show a single feature that resembles the bonding dipole plasmon (BDP) mode. A configuration interaction (CI) analysis shows that the BDP mode arises from constructive coupling of transitions, whereas the destructive coupling does not produce significant oscillator strength for such separation distances. At shorter separation distances, both constructive and destructive coupling produce oscillator strength due to wave-function overlap, which results in multiple features in the calculated spectra. Our analysis shows that a charge-transfer plasmon (CTP) mode arises from destructive coupling of transitions, whereas the BDP results from constructive coupling of the same transitions at shorter separation distances. Furthermore, the coupling elements between these transitions are shown to depend heavily on the amount of exact Hartree-Fock exchange (HFX) in the functional, which affects the splitting of CTP and BDP modes. With 50% HFX or more, the CTP and BDP modes mainly merge into a single feature in the spectra. These findings suggest that the effects of exact exchange must be assessed during the prediction of CTP modes in plasmonic systems.