Danai Topouza, MSc
I am a bioinformatician trained in molecular biology and computer science. My expertise lies in using statistical and machine learning approaches to investigate disease phenotypes. I have extensive experience in the analysis of complex biological datasets with multi-omic modalities. I hope to use my multidisciplinary expertise to contribute to innovations in therapeutics that improve patients’ lives.
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https://orcid.org/0000-0002-6897-9281
Education
2021 - 2023: PhD in Human Genetics, McGill University
2017 - 2019: MSc in Bioinformatics and Experimental Medicine, Computational Genomics Laboratory, Queen's University
2013 - 2017: BScH, Major in Biology and Minor in Computer Science, Queen's University
Research
My PhD project investigated the composition of the tumor immune microenvironment in pediatric high-grade gliomas.
My previous work investigated the biological networks and genomic variants that modulate first-line chemotherapy response in ovarian cancer patients. Through analysis of next-generation sequencing patient data, I discovered integrated gene and microRNA expression networks, genomic variants, and expression quantitative trait loci that are associated with chemotherapy resistance.
In addition, I have worked with several types of bioinformatics data and analytical methods, including the preprocessing and analysis of DNA methylation data in hepatocellular carcinoma and circadian rhythm projects, the RNA-seq analysis of the response to a novel combination treatment in chronic myeloid leukemia, genome-wide (GWAS) and phenome-wide association studies (PheWAS) in the CHILD Study Cohort, and the time-series integration of mRNA and microRNA in murine brain tissues to identify transcripts under circadian control.
Publications
1. Novel microRNA-regulated transcript networks are associated with chemotherapy response in ovarian cancer.
Topouza DG, Choi J, Nesdoly S, Tarnouskaya A, Nicol CJB, Duan QL.
International Journal of Molecular Sciences (2022). https://doi.org/10.3390/ijms23094875
2. Investigating the relationship between melatonin patterns and methylation in circadian genes among day shift and night shift workers.
Ritonja JA, Aronson KJ, Leung M, Flaten L, Topouza DG, Duan QL, Durocher F, Tranmer JE, Bhatti P.
Occupational and Environmental Medicine (2022). https://doi.org/10.1136/oemed-2021-108111
3. DNA methylation of circadian genes and markers of cardiometabolic risk in female hospital workers: An exploratory study.
3. Ahmadi SA, Tranmer JE, Ritonja JA, Flaten L, Topouza DG, Duan QL, Durocher F, Aronson KJ, Bhatti P.
Chronobiology International (2022). https://doi.org/10.1080/07420528.2022.2032729
4. Exploring the impact of night shift work on methylation of circadian genes.
Ritonja J, Aronson KJ, Flaten L, Topouza DG, Duan QL, Durocher F, Tranmer JE, Bhatti P.
Epigenetics (2021). https://doi.org/10.1080/15592294.2021.2009997
5. Gene networks and expression quantitative trait loci associated with adjuvant chemotherapy response in high-grade serous ovarian cancer.
Choi J, Topouza DG,Tarnouskaya A, Nesdoly S, Koti M, Duan QL.
BMC Cancer (2020). https://doi.org/10.1186/s12885-020-06922-1