Master Degree / Yüksek Lisans Tezleri

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Access Right: Open AccessSubject: search.filters.subject.Small interfering RNA

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  • Master Thesis
    In Vitro Evaluation of Poly (2-((2 Amino) Ethyl Methacrylate) as a Potential Sirna Delivery Agent
    (Izmir Institute of Technology, 2015) Seyrantepe, Volkan; Seyrantepe, Volkan; Bulmuş Zareie, Volga; Bulmuş Zareie, Esma Volga; Seyrantepe, Volkan; 03.01. Department of Bioengineering; 04.03. Department of Molecular Biology and Genetics; 03. Faculty of Engineering; 04. Faculty of Science; 01. Izmir Institute of Technology
    The aim of this thesis is to investigate poly(2-((2-aminoethyl)amino)ethyl methacrylate) (P(AEAEMA)) as a potential siRNA carrier. For this purpose, an amine containing monomer 2-((tert-butoxycarbonyl) (2-((tert-butoxy carbonyl) amino) ethyl) amino) ethyl methacrylate (BocAEAEMA) was synthesized. Reversible addition-fragmentation chain transfer (RAFT) polymerization was performed to prepare homo- and block co-polymers of BocAEAEMA. The synthesized polymers -P(AEAEMA)19, P(AEAEMA)41 and P(PEGMA)12-b-P(AEAEMA)32- were characterized via NMR and GPC. The cytotoxicity of the polymers was investigated in vitro using ovarian cancer cell line (Skov-3-luc) via MTT assay. The polymers did not show any toxic effect on cells in 24 h. The ability of the BocAEAEMA polymers to form polyplexes with siRNA was investigated via gel electrophoresis. P(AEAEMA)19, P(AEAEMA)41 and P(PEGMA)12-b-P(AEAEMA)32 could efficiently form complexes with siRNA at an N/P ratio of 5, 2, and 2 respectively. Gel electrophoresis analysis revealed that P(AEAEMA)41 and P(PEGMA)12-b-P(AEAEMA)32 could protect siRNA against serum components at least for 6 h. Block copolymer, when complexed with siRNA at an N/P ratio of 10, could protect siRNA longer (24 h) when compared with the homopolymer. The size and surface charge of the polyplexes were investigated by DLS. The diameter of the P(AEAEMA)41-siRNA complexes was found to be lower than 110 nm at all N/P ratios tested. In contrast, P(PEGMA)12-b-P(AEAEMA)32-siRNA complexes (except the complex prepared at the N/P ratio of 2), displayed aggregation tendency. All polyplexes displayed positive zeta potential. The zeta potential of the homopolymer was found to be higher than the copolymer at the N/P ratio of 2. Finally, in order to determine siRNA transfection ability of the polymers, luciferase assay was optimized using a commercial transfection reagent lipofectamine RNAimax. The optimized assay conditions will be used in future studies to determine the transfection efficiency of the polymers.
  • Master Thesis
    An Integrative Data Mining Approach for Microrna Detection in Human
    (Izmir Institute of Technology, 2013) Saçar, Müşerref Duygu; Allmer, Jens; Allmer, Jens; 04.03. Department of Molecular Biology and Genetics; 04. Faculty of Science; 01. Izmir Institute of Technology
    MicroRNAs (miRNAs) are single-stranded, small, usually non-coding RNAs of about 22 nucleotides in length, that control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, or destabilization of their target mRNAs. Although hundreds of miRNAs have been identified in various species, many more may still remain unknown. Therefore, the discovery of new miRNA genes is an important step for understanding miRNA mediated post transcriptional regulation mechanisms. First attempts for the identification of novel miRNA genes were almost exclusively based on directional cloning of endogenous small RNAs and high-throughput sequencing of large numbers of cDNA clones. However, conventional forward genetic screening is known to be biased towards abundantly and/or ubiquitously expressed miRNAs that can dominate the cloned products. Hence, such biological approaches might be limited in their ability to detect rare miRNAs, and restricted to the tissues and the developmental stage of the organism under examination. These limitations have led to the development of sophisticated computational approaches attempting to identify possible miRNAs in silico. Nevertheless, the programs designed to predict possible miRNAs in a genome are not sensitive or accurate enough to warrant sufficient confidence for validating all their predictions experimentally. With this study, we aim to solve these problems by developing a new and sensitive machine learning based approach to predict potential miRNAs in the human genome.