Browsing by Subject "Bioinformatic"

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Open Access
Effects of aging on gene expression levels of inflammatory, cytoskeletal and microglial markers in the brain using the zebrafish (Danio Rerio) model organism
(2021-01) Aydoğan, Hande Özge
Age-related cognitive decline burdens the elderly population, limiting their abil-ity to socialize and be independent. To be able to develop proper treatments, healthy aging should be examined. Previous studies focusing on healthy brain aging revealed that abnormal microglial activation was observed. Aging microglia exhibits 0partial loss of motility due to cytoskeletal changes, leading to decreases in their ability to respond to environmental cues. Thus, a more inﬂammatory phe-notype was observed in microglia. These disruptions of the previously established homeostasis in the brain could be the underlying reason for cognitive decline ex-perienced during aging. To understand these changes during aging in the brain, cytoskeletal, microglial, and inﬂammation-related markers were investigated by using both in silico and in vivo approaches. In silico analyses were performed on mice hippocampus and the whole brain revealed that the genes involved in the actin cytoskeleton reorganization (Arpc1b), neurogenesis (Erbb4), and proinﬂam-matory related pathways (Il1b, P2x7r, Elf2b) showed diﬀerential gene expression levels among diﬀerent age groups, genders, and tissue of origin. On the other hand, no diﬀerential expression was observed in microglial (Coro1a and Aif1) and anti-inﬂammatory markers (Tgfb1 and Il10). To further validate these re-sults in vivo, quantitative polymerase chain reaction (qPCR) was performed on young and old zebraﬁsh brains. According to the results, only two genes showed marginally signiﬁcant diﬀerences among young and old brains: arpc1b and p2x7r. These results collectively could mean 1) the overall microglia population does not change during aging, 2) the brain does not exhibit imbalances in terms of pro-and anti-inﬂammatory cytokines, and 3) neurogenesis. Furthermore, the signiﬁ-cant changes observed in arpc1b and p2x7r indicated the iii iv importance of the cytoskeleton and inﬂammation-related pathways in the correct functioning of the cells. Therefore, this study showed that in silico analysis are the reliable indica-tors of in vivo experiments, zebraﬁsh can be used as a gerontological model, and the importance of cytoskeleton in motile cells. However, to understand these de-scribed relations, further investigation on the protein level of these genes should be done.
Open Access
PAMOGK-Web: a framework for cancer subtype identification using copy number variatıons
(2020-12) Akdemir, Furkan Mustafa
Detection of molecular sub-groups of cancer is important for developing cancer therapeutics and to understand the underlying causes of the molecular diﬀerences in these groups. The cancer sequencing projects made multi-omics data available for large cancer cohorts. The multi-omics data provides multiple views into the cancer which can be used to ﬁnd underlying causes from diﬀerent perspectives and capture relations not possible with a single view approach. Previously, we developed a pipeline that uses multi-omics data to detect sub-groups of patients called PAMOGK. PAMOGK forms multiple views of the patients using pathways and multi-omics data and assess patient similarities under these views. PAMOGK was designed as a general framework that can be used to map many diﬀerent omics data but was experimented with mutation, transcriptome, and proteome. In this work, we extend the use of PAMOGK with copy number variation data which shows comparable results to experiments without it. As a second contribution, we provide a web framework designed for PAMOGK easier to make it accessible to general users: PAMOGK-Web. This new web based framework is able to abstract the PAMOGK pipeline and provide a simple interface to run experiments and return results to the users. PAMOGK-Web will be using the generic design of PAMOGK to provide ready to use experiments that include setups using diﬀerent omics data.