PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Predicting Respiratory Infection and Symptoms Development Using Gene Set Enrichment Scores and Machine Learning(Elsevier Sci Ltd, 2026) Aydin, Zafer; Isik, Yunus EmreRecent advancements in precision medicine enable personalized predictions grounded in individual-level genetic data. However, relying solely on a single type of data can decrease prediction accuracy and limit the biological interpretability of the resulting models. Incorporating predefined genetic knowledge, such as derived gene sets, can improve performance and provide deeper biological insights for complex diseases, including respiratory infections. This study aimed to evaluate the usability of enrichment scores (ES), calculated using gene sets from the Molecular Signatures Database (MSigDB), as a feature representation for machine learning models to predict respiratory viral infections and symptom development. In addition, the proposed feature representation approach was extensively compared with the de facto gene-level expression representation. A total of 36,834 predefined gene sets were compiled from the MSigDB, and their ES values were calculated. Experiments used the GSE73072 dataset from Gene Expression Omnibus, containing gene expression profiles before and after virus exposure. Various machine learning and feature selection algorithms were applied to ES-based and probe-level feature sets. The results showed that both feature representation approaches achieved an area under the precision-recall curve (AUPRC) value greater than 0.90 for all tasks. Compared with the Respiratory Viral DREAM Challenge leaderboard phase, our models showed a 14.8% improvement in pre-exposure predictions (T0) and a 17.4% improvement in symptom classification. Using enrichment scores as a feature representation generally resulted in better performance than probe-level representation when predicting respiratory infections and symptom development. Identifying key gene sets through feature selection and comparing them with essential genes for respiratory viruses enabled a more comprehensive analysis, providing deeper insights into the pathways that contribute to these predictions.Article Integrative Bioinformatics Prediction of West Nile Virus-Derived microRNAs Reveals Potential Host Regulatory Interactions(Elsevier Sci Ltd, 2026-08) Demirci, Muserref Duygu Sacar; Orhan, Mehmet Emin; Erginkoc, Altay Nida; Saçar Demirci, Müşerref DuyguWest Nile virus (WNV) is a mosquito-borne flavivirus linked to severe neuroinvasive disease. Although host and vector microRNAs (miRNAs) have been implicated in viral infection, the presence and functional relevance of WNV-encoded miRNAs remain largely unexplored. Here, we developed an integrative bioinformatics pipeline that combines multiple miRNA prediction algorithms with secondary structure screening and host transcriptomic data to identify high-confidence candidate WNV-derived mature miRNAs. Overlap-based confidence scoring and differential expression support from RNA-seq datasets prioritized a small subset of putative miRNA-mRNA interactions with potential roles in infection-associated gene regulation. A competitive endogenous RNA network constructed from predicted mRNA, lncRNA, and circRNA targets highlighted pathways involving innate immunity, GPCR and Wnt signaling, RNA degradation, and viral replication. Together, these findings provide a reproducible computational workflow and nominate testable regulatory interactions for future experimental validation.Article Citation - WoS: 42Citation - Scopus: 57What 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: 34Citation - Scopus: 45Strategy Implementation Research in Hospitality and Tourism: Current Status and Future Potential(Elsevier Sci Ltd, 2020-07) Aladag, Omer Faruk; Koseoglu, Mehmet Ali; King, Brian; Mehraliyev, FuadTo achieve their business objectives, hospitality and tourism organizations need effective implementation as well as consistent strategy formulation. However, the implementation aspect of strategy has attracted relatively less scholarly interest than strategic planning despite its critical role in achieving performance outcomes. Consequently, it is timely to provide an in-depth analysis of the strategy implementation literature. This is particularly the case in hospitality and tourism management where comprehensive literature reviews of strategy implementation have been lacking. To address the knowledge gap, the authors conduct a systematic literature review of 139 articles that appeared in 42 journals over the period 1988-2019. The items were grouped into six topic clusters with a view to generating novel research questions that have the potential to advance the field. We identify four main gaps that should be addressed and suggest prospective research directions.Article Citation - WoS: 32Citation - Scopus: 32Revisiting the Nexus Among Carbon Emissions, Energy Consumption and Total Factor Productivity in African Countries: New Evidence from Nonparametric Quantile Causality Approach(Elsevier Sci Ltd, 2020-03) Dogan, Eyup; Tzeremes, Panayiotis; Altinoz, BuketThis study aims to contribute to the existing thin body of nonlinear causality literature by applying the new hybrid nonparametric quantile causality approach. In this line, we investigate the non-linear nexus among total factor productivity, energy consumption and carbon emissions for seventeen African countries. From the results, it is remarkable that there are generally strong causalities between the variables in the middle lower, middle upper and middle quantiles. Hence, energy consumption, environmental pollution and total factor productivity are closely linked in African countries. In particular, bidirectional linkage is detected between total factor productivity and energy consumption for Angola, Benin, Botswana, Cote d'Ivoire, Kenya, Morocco, Egypt, Nigeria and Tunisia. Studying the relationship between total factor productivity and emissions again at the middle quantile bidirectional causal ordering is documented almost for all the countries. Lastly and regarding the linkage between energy consumption and carbon emissions, a strong bidirectional ordering between the two variables is confirmed for Angola, Benin, Cote d'Ivoire, Cameroon, Kenya, Morocco, Egypt, Mozambique, Nigeria, Senegal and Tunisia. We can notice that an increase in economic development is critical for these countries; a number of regulatory policies for environmental problems and energy consumption are required during this development.Article Citation - WoS: 39Citation - Scopus: 38Analyzing the Nexus of COVID-19 and Natural Resources and Commodities: Evidence From Time-Varying Causality(Elsevier Sci Ltd, 2022-08) Dogan, Eyup; Majeed, Muhammad Tariq; Luni, TaniaEven though a few studies have focused on natural resources and commodity sectors by considering the pandemic, they have only compared their status in pre-COVID19 to post-COVID19. None of the studies has directly examined the causal relationship between the pandemic, and natural resource index and the primary commodity-related sector indices. This study fills the gap of exploring the dynamic association between them by analyzing the causal relationship between the COVID19, and natural resources index and the primary commodity-related sectors (i.e., agribusiness, energy, and metals & mining) by applying a novel time-varying causality test on daily data from January 23, 2020, to November 12, 2021. The empirical results support the presence of time-varying causality from COVID19 to natural resources, agribusiness, energy and metals & mining. The results obtained from the rolling window algorithm support causal linkages between the variables however at several points it fails to capture the dynamics of linkages between the variables which is captured by the recursive window algorithm. The outcome is robust when the pandemic is proxied by either number of cases or deaths. Similarly, the findings obtained from heteroskedastic-robust specification also validate our findings. Several policy implications are further discussed in the study.Article Citation - WoS: 36Citation - Scopus: 41AirBNB and COVID-19: Space-Time Vulnerability Effects in Six World-Cities(Elsevier Sci Ltd, 2022-12) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, UmutThis study examines the COVID-19 vulnerability and subsequent market dynamics in the volatile hospitality market worldwide, by focusing in particular on individual Airbnb bookings-data for six world-cities in various continents over the period January 2020-August 2021. This research was done by: (i) looking into factual survival rates of Airbnb accommodations in the period concerned; (ii) examining place-based impacts of intracity location on the economic performance of Airbnb facilities; (iii) estimating the price responses to the pandemic by means of a hedonic price model. In our statistical analyses based on large volumes of time- and space-varying data, multilevel logistic regression models are used to trace `corona survivability footprints' and to estimate a hedonic price-elasticity-of-demand model. The results reveal hardships for the Airbnb market as a whole as well as a high volatility in prices in most cities. Our study highlights the vulnerability and `corona echoeffects' on Airbnb markets for specific accommodation segments in several large cities in the world. It adds to the tourism literature by testing the geographic distributional impacts of the corona pandemic on customers' choices regarding type and intra-urban location of Airbnb accommodations.