Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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

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  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 8
    Distinguishing Between Microrna Targets From Diverse Species Using Sequence Motifs and K-Mers
    (SCITEPRESS, 2017) Yousef, Malik; Khalifa, Waleed; Acar, İlhan Erkin; Allmer, Jens
    A disease phenotype is often due to dysregulation of gene expression. Post-translational regulation of protein abundance by microRNAs (miRNAs) is, therefore, of high importance in, for example, cancer studies. MicroRNAs provide a complementary sequence to their target messenger RNA (mRNA) as part of a complex molecular machinery. Known miRNAs and targets are listed in miRTarBase for a variety of organisms. The experimental detection of such pairs is convoluted and, therefore, their computational detection is desired which is complicated by missing negative data. For machine learning, many features for parameterization of the miRNA targets are available and k-mers and sequence motifs have previously been used. Unrelated organisms like intracellular pathogens and their hosts may communicate via miRNAs and, therefore, we investigated whether miRNA targets from one species can be differentiated from miRNA targets of another. To achieve this end, we employed target information of one species as positive and the other as negative training and testing data. Models of species with higher evolutionary distance generally achieved better results of up to 97% average accuracy (mouse versus Caenorhabditis elegans) while more closely related species did not lead to successful models (human versus mouse; 60%). In the future, when more targeting data becomes available, models can be established which will be able to more precisely determine miRNA targets in hostpathogen systems using this approach.
  • Conference Object
    Terahertz Transmission Through Patterened Vanadium Oxide Thin Films on Dielectric Substrates
    (SCITEPRESS, 2017) Akkaya, M.; Demirhan, Yasemin; Yüce, Hürriyet; Aygün, Gülnur; Özyüzer, Lütfi; Sabah, Cumali; Altan, Hakan
    Patterned and unpatterned films of vanadium oxide grown on dielectric substrates such as fused silica and sapphire were grown and analysed by varying the temperature using terahertz time domain spectroscopy. After investigating the critical transition temperature near 340K, a well-known cross-shaped pattern was studied to observe any resonances upon transmission. Due to the poor conductivity of the films the frequency selective nature of the structure was not observed, however an etalon effect could be seen in the sapphire substrate as opposed to the fused silica substrate above the critical temperature. Dependence of the refractive index difference between substrates upon transmission of the THz pulse is likely in explaining this observed difference.
  • Conference Object
    Citation - Scopus: 4
    Itemset Hiding Under Multiple Sensitive Support Thresholds
    (SCITEPRESS, 2017) Öztürk, Ahmet Cumhur; Ergenç Bostanoğlu, Belgin
    Itemset mining is the challenging step of association rule mining that aims to extract patterns among items from transactional databases. In the case of applying itemset mining on the shared data of organizations, each party needs to hide its sensitive knowledge before extracting global knowledge for mutual benefit. Ensuring the privacy of the sensitive itemsets is not the only challenge in the itemset hiding process, also the distortion given to the non-sensitive knowledge and data should be kept at minimum. Most of the previous works related to itemset hiding allow database owner to assign unique sensitive threshold for each sensitive itemset however itemsets may have different count and utility. In this paper we propose a new heuristic based hiding algorithm which 1) allows database owner to assign multiple sensitive threshold values for sensitive itemsets, 2) hides all user defined sensitive itemsets, 3) uses heuristics that minimizes loss of information and distortion on the shared database. In order to speed up hiding steps we represent the database as Pseudo Graph and perform scan operations on this data structure rather than the actual database. Performance evaluation of our algorithm Pseudo Graph Based Sanitization (PGBS) is conducted on 4 real databases. Distortion given to the nonsensitive itemsets (information loss), distortion given to the shared data (distance) and execution time in comparison to three similar algorithms is measured. Experimental results show that PGBS is competitive in terms of execution time and distortion and achieves reasonable performance in terms of information loss amongst the other algorithms. © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.