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Recent Submissions

ItemOpen Access
Investigation of the generation effect on memory and metamemory through semantic and perceptual cues
(Bilkent University, 2024-04) Yavuz, Fatih Tayyip
The generation effect is an experimental finding that self-generated information produces higher memory performance than reading. The effect can be obtained through various semantic and perceptual generation manipulations. Despite numerous studies investigating semantic and perceptual generation tasks separately, studies have not compared the effectiveness of the two formats directly. For Experiment 1, participants read or generated words from rhyming words or highly associated words, comprising a 2 (level of processing: perceptual, semantic) x 2 (generation status: generation, read) within-subjects design. The results showed that participants had higher memory performance for generated words than for words that were read. Moreover, an interaction revealed that memory performance was higher for the semantic generation task than for the perceptual generation task. Experiment 2 aimed to investigate participants’ memory predictions for perceptual and semantic generation tasks. Moreover, we investigated whether making predictions modifies memory performance. Experiment 2 incorporated judgments-of-learning (JOL) and no-JOL groups, yielding that participants accurately predicted and performed better on memory tasks involving generation and semantic manipulations. Additionally, the cued-recall retrieval phase produced higher memory performance for the JOL-group than the no-JOL group, suggesting that predicting one's memory performance enhances actual memory performance. Experiment 3 aimed to see the importance of the test type for the metamemory reactivity. Like Experiment 2, the JOL group still had a higher memory performance than the no-JOL group. The group difference was only observable during a semantic cued-recall test, implying the test type's importance.
TP53 META, A webtool to visualize effects of TP53 modulators and mutations on expression profiles with a focus on breast cancer
(Bilkent University, 2024-05) Aftab, Abdul Moiz
Compilation and comparison of multiple datasets that relate to a particular treatment can help us understand more about a scientific question of interest. Transcription factor protein 53 (TP53), also known as the “Guardian of the genome”, is one of the most mutated transcription factors in sporadic Breast Cancer. Even though there are multiple online databases that compile, annotate and list p53 targets, these gene lists can vary significantly and no web-tool is available to visualize them and perform a meta-analysis of their expressions. Herein, I have developed an R Shiny based tool called TP53 META that allows for comparison and visualization of up to four separate, two group RNA-seq datasets. TP53 META is able to normalize and perform differential expression analysis via limma or DESeq2 on different datasets, simultaneously. Moreover, it allows users to perform clustering, gene-set enrichment analyses, transcription factor-target enrichment, as well as visualization by using disease-gene and treatment-gene bipartite networks that can be generated for further understanding of individual or combination treatments. It is also possible to limit the use of TP53 META modules to a subset of the transcriptome, e.g., specific targets of p53 such as DREAM targets. TP53 META also calculates a meta-p-value using different available meta-analysis statistical methods and incorporates several public as well as in house datasets, most of which are of breast cancer cell lines, in which TP53 is modulated by siRNA treatments, inducers such as nutlin, doxorubicin, CHRNA5 depletion, or stable mutations in the heterozygous or homozygous background. Public datasets were acquired from GEO while for in house datasets, I have obtained the fastq files and converted to counts and integrated them on TP53 META web-tool and tested the following hypotheses to demonstrate the functionality of the web-tool: 1) Does CHRNA5 depletion, a known TP53 inducer, result in further downregulation of DREAM targets in MCF7 with the wildtype TP53 or heterozygous TP53 mutant MCF7 cells?; 2) Do TP53 inducers induce TP53 targets equally in wild type and mutant cancer cells? I also applied existing and novel methods to determine synergistic/antagonistic relationship of genes between the two treatments, e.g., doxorubicin alone or doxorubicin together with CHRNA5 depletion. Results showed that wildtype homozygous TP53 overexpression depletes DREAM targets more than heterozygous mutant MCF7 cells where a copy of mutant TP53 (R175H, R273H) exists. I have also found that CHRNA5 depletion in combination with doxorubicin can further regulate certain TP53 targets.
CAP-RNAseq: an online platform for RNA-seq data clustering, annotation and prioritization based on gene essentiality and congruence between mRNA and protein levels
(Bilkent University, 2024-04) Özdeniz, Merve Vural
In recent years, there has been a remarkable growth in the application of RNA-seq in both clinical and molecular biology research contexts. The analysis and interpretation of these RNA-seq data demands a good knowledge of bioinformatics. Many different applications are available to perform the analysis, but more comprehensive applications are needed, especially for researchers without coding experience. Therefore, I developed an all-in-one novel RNA-seq analysis tool, CAP-RNAseq (, which provide valuable analysis for co-expression cluster prioritization and annotation. CAP-RNAseq in particular performs clustering of the genes based on their expression patterns, annotates mirror clusters that display inverse patterns with a network-based visualizations before prioritization of clusters and/or genes based on "gene essentiality", protein levels and the degree of congruence between mRNA and protein levels of genes. Furthermore, for illustration of the use of CAP-RNAseq in this thesis, I reanalyzed a number of published RNA-seq datasets and identified novel pathways modulated by NTRK2 overexpression (GSE136868) in neural stem cells and also showed significance of the essential genes/pathways in senescent cell clearance focusing on NTRK2 (fibroblast; GSE190998) and THBD (Huh7, GSE228941) siRNA models. In addition, I analyzed our lab’s novel RNA-seq data obtained from breast cancer cell lines in CAP-RNAseq; and the findings revealed a) the complex associations between steroid hormones; Drospirenone, Aldosterone, and Estrogen in hormone positive T47D and mineralocorticoid receptor-overexpressing MCF-7 cells; and b) significant differences in essential and non-essential gene expression of the isogenic MCF7 cells overexpressing wildtype or mutant TP53. I also studied a public breast cancer dataset (GSE201085) demonstrating CAP-RNAseq’s ability to identify novel breast cancer markers exhibiting high mRNA-protein level correlations. In conclusion, this thesis not only demonstrates the use and power of CAP-RNAseq as a tool to identify essential genes and pathways by analyzing RNA-seq data, but also provides new insights into the roles of essential genes in glioma, senescence and breast cancer.
ItemOpen Access
The Carbon markets and their effects on climate justice
(Bilkent University, 2024-03) Tekin, Emirhan
The carbon markets are the most popular climate policy for reducing greenhouse gas emissions. They are the profit-based markets which prioritize cost-efficiency rather than climate justice, and environmental additionality. As an intra-system solution, the carbon markets present all the problems and contradictions of the neoliberal environmental policies. This thesis questions the effects of the carbon markets on climate justice. It argues that the carbon markets have been deepening and increasing climate injustice due to their profit-based neoliberal features. Subsequently, the unequal representation on the international and local climate politics, commodified characteristic of carbon and offsetting mechanisms contribute to increase climate injustice. To analyze and clarify those effects on the carbon markets, this thesis discusses three cases: California Cap and Trade Program, the impacts of the CDM projects in China, and REDD+ projects. Those three cases are the examples of the most applied three mechanisms: Emission Trading System, Clean Development Mechanism, and Voluntary Carbon Mechanism. Those three cases indicate how and why the carbon markets deepen and increase climate injustice. The thesis explores the limitations and problems of market-driven environmental policies.
ItemOpen Access
Shared secrets: (Re)writing urban mysteries in nineteenth-century İstanbul
(Edinburgh University Press, 2022-12-31) Şimşek, Şehnaz Şişmanoğlu; Charrière, Etienne; Booth, Marilyn; Savina, Claire