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Your search keyword '"Karlik A"' showing total 132 results
Start Over Author "Karlik A" Publisher elsevier b.v.
132 results on '"Karlik A"'

28. Endogenous retrovirus HERV-K6 and HERV-K11 polymorphisms’ analyses in head and neck squamous cell carcinoma patients

Author

Orkun Gurbuz, Elif Karlik, Nermin Gozukirmizi, Yemliha Yildiz, İstinye Üniversitesi, Sağlık Hizmetleri Meslek Yüksekokulu, Eczane Hizmetleri Bölümü, Elif Karlık / 0000-0003-0669-2725, Orkun Gürbüz / 0000-0001-7488-4361, Yemliha Yıldız / 0000-0002-1741-0503, Karlık, Elif, Gürbüz, Orkun, Yıldız, Yemliha, Gözükırmızı, Nermin, Elif Karlık / GCA-4597-2022, Orkun Gürbüz / AGW-8435-2022, Yemliha Yıldız / CIP-3948-2022, Nermin Gözükırmızı / DXX-2404-2022, Elif Karlık / 56926577900, Orkun Gürbüz / 57225777041, Yemliha Yıldız / 35222814800, and Nermin Gözükırmızı / 6701520637

Subjects
0301 basic medicine, viruses, Endogenous retrovirus, HNSCC, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Polymorphism (computer science), IRAP, Genetics, Medicine, Polymorphism, Genetics (clinical), business.industry, Melanoma, Endogenous Retroviruses, Cancer, medicine.disease, Head and neck squamous-cell carcinoma, 030104 developmental biology, 030220 oncology & carcinogenesis, embryonic structures, Cancer research, HERV, Germ cell tumors, business, Ovarian cancer
Abstract

Many tumors, such as melanoma, breast cancer, germ cell tumors, renal cancer or ovarian cancer, express HERV proteins, mainly HERV-K (HML6) and HERV-K (HML2). However, there is no report showing any relation between squamous cell carcinoma of head and neck (HNSCC) and HERVs in literature. Here we report the polymorphic changes of HERV-K6 and HERV-K11 in tumor tissue samples of HNSCC patients comparing with healthy individuals. For this purpose, genomic DNAs from tumor tissue samples of 2 healthy individuals and of 8 HNSCC patients were isolated and IRAP-PCR was performed. IRAP-PCR analyses demonstrated that there were 18–73% polymorphism rates for HERV-K6 and 38–100% polymorphism rates for HERV-K11 among all the samples. There were also polymorphic changes between two control materials. Therefore, HERV-K6 polymorphisms may arise on an individual-specific basis. In the previous studies, some associations have been reported between the expression of HERVs and some cancer types or other major diseases. However, few reports have analyzed HERV-K movements among HNSCC patients. This report is the first study investigating HERV-K6 and HERV-K11 retrotransposon polymorphic changes in HNSCC patients. WOS:000641584300007

Published
2021

50. Robust adaptive learning approach to self-organizing maps.

Author

Ali Hameed, Alaa, Karlik, Bekir, Salman, Mohammad Shukri, and Eleyan, Gülden

Subjects
*SELF-adaptive software, *SELF-organizing maps, *LEARNING
Abstract

Abstract The Self-Organizing Map (SOM) has attracted much research in diverse fields of study, where it has been successfully applied to a wide range of artificial intelligence applications. In this paper, a new intelligent adaptive learning SOM, in contrast with the conventional SOM algorithm, is presented. The proposed SOM overcomes the disadvantages of the conventional SOM by deriving a new variable learning rate that can adaptively achieve the optimal weights and obtain the winner neurons with a shorter learning process time. To quantify the performance, the proposed SOM was compared with various unsupervised algorithms to examine how well the network weight update equation adapts and reaches the optimum weights with fewer iterations. Extensive experiments were conducted using eight different databases from the UCI and KEEL repositories. The proposed SOM algorithm was further compared with the conventional SOM, GF-SOM, PLSOM, and PLSOM2 algorithms. The proposed SOM algorithm showed superiority in terms of the convergence rate, Quantization Error (QE), Topology Error (TE) preserving map, and accuracy during the classification process. [ABSTRACT FROM AUTHOR]

Published
2019
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