PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
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Article Citation - Scopus: 19Feature Selection Has a Large Impact on One-Class Classification Accuracy for Micrornas in Plants(Hindawi Publishing Corporation, 2016) Yousef, Malik; Demirci, Müşerref Duygu Saçar; Khalifa, Waleed; Allmer, JensMicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of 95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.Article Citation - WoS: 7Citation - Scopus: 8Mir-17 in Imatinib Resistance and Response To Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia Cells(Zerbinis Medical Publications, 2013) Fıratlıgil, Burcu; Biray Avcı, Çığır; Baran, YusufIn this study we examined the expression levels of miR-17 which possesses oncogenic activities through downregulation of CDKN1A, p21 and E2F1 tumor suppressor genes, in imatinib sensitive and resistant chronic myeloid leukemia (CML) cells. On the other hand, we also determined the expression levels of miR-17 in response to tyrosine kinase inhibitors imatinib, nilotinib and dasatinib used for the treatment of CML. Methods: The expression profiles of miR-17 were analysed by Stem-Loop reverse transcription (RT) polymerase chain reaction (PCR). Results: The results revealed significant increase in the expression levels of miR-17 in imatinib sensitive and resistant cells compared to peripheral blood mononuclear cells (PBMCs). On the other hand, significant decrease was observed in miR-17 levels in response to imatinib, nilotinib and dasatinib. Conclusion: These results may imply that miR-17 can be used for diagnosis and treatment of CML.