Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Citation - Scopus: 4
    Quasi-Supervised Strategies for Compound-Protein Interaction Prediction
    (John Wiley and Sons Inc, 2022) Çakı, O.; Karaçalı, B.
    In-silico compound-protein interaction prediction addresses prioritization of drug candidates for experimental biochemical validation because the wet-lab experiments are time-consuming, laborious and costly. Most machine learning methods proposed to that end approach this problem with supervised learning strategies in which known interactions are labeled as positive and the rest are labeled as negative. However, treating all unknown interactions as negative instances may lead to inaccuracies in real practice since some of the unknown interactions are bound to be positive interactions waiting to be identified as such. In this study, we propose to address this problem using the Quasi-Supervised Learning (QSL) algorithm. In this framework, potential interactions are predicted by estimating the overlap between a true positive dataset of compound-protein pairs with known interactions and an unknown dataset of all the remaining compound-protein pairs. The potential interactions are then identified as those in the unknown dataset that overlap with the interacting pairs in the true positive dataset in terms of the associated similarity structure. We also address the class-imbalance problem by modifying the conventional cost function of the QSL algorithm. Experimental results on GPCR and Nuclear Receptor datasets show that the proposed method can identify actual interactions from all possible combinations. © 2021 Wiley-VCH GmbH.
  • Article
    Citation - Scopus: 10
    Use of Magic Sandwich Echo and Fast Field Cycling Nmr Relaxometry on Honey Adulteration With Corn Syrup
    (John Wiley and Sons Ltd, 2022) Berk, B.; Cavdaroglu, C.; Grunin, L.; Ardelean, I.; Kruk, D.; Mazi, B.G.; Oztop, M.H.
    BACKGROUND: Adulteration is defined as the intentional addition of a material that is not a part of the nature. In this study, a non-conventional time domain nuclear magnetic resonance (TD-NMR) pulse sequence: magic sandwich echo (MSE) was used to detect the adulteration of honey by glucose syrup (GS) and high fructose corn syrup (HFCS) accompanied with T1 and T2 relaxation times. Also, fast field cycling NMR (FFC-NMR) relaxometry and multivariate analysis were performed to investigate the adulteration. RESULTS: Higher maltose in GS and changing glucose to water ratio of HFCS gave high correlation with the crystal content values. In HFCS adulteration, two separate populations of protons having different T2 values were detected and T1 times were also used to determine GS adulteration. Addition of GS increased T1 while addition of HFCS increased T2, significantly. CONCLUSION: The results showed that it is possible to differentiate the unadulterated and adulterated honey samples by using TD-NMR relaxation times and crystal content values obtained by the MSE sequence. By FFC-NMR relaxometry, not only GS addition but also the amount of GS was examined. The multivariate analysis technique of principal component analysis was able to distinguish the types of adulterants. © 2021 Society of Chemical Industry. © 2021 Society of Chemical Industry.