One goal of our laboratory is to elucidate the molecular mechanisms of chemotherapy resistance in ovarian cancer.
Another goal is to use bioinformatic tools to understand genomic factors that drive tumor progression.
We are also manipulating gene expressions to enhance the efficacy of chemotherapeutic agents and contribute to cancer treatment modalities.
Our research mainly focuses on chemoresistance and DNA repair mechanisms in ovarian cancer. Our laboratory also studies molecular changes in the components of apoptotic and pyroptotic cell death pathways in ovarian cancer using transcriptomics datasets and in vitro models. We aim to identify molecular events contributing to the development of cancer and its progression to a more aggressive disease. We mostly utilize cell culture techniques and data science tools to better understand these events observed as changes at the transcript or protein levels. We perform experiments to obtain mechanistic insights into pyroptosis and its downstream molecular processes in this largely understudied cancer type with the ultimate aim of developing novel treatment strategies to this most lethal gynecological malignancy.
We also utilize different data science tools and big data to better understand molecular dynamics of cancer in terms metastasis, progression and evolution. Furthermore, our research covers the molecular studies on cancer types other than gynecological cancers.
In addition, our research interests range from aging to ecological data science. We mainly use publicly available datasets to make the most out of these data using R statistical programming language. We approach these datasets from different angles to answer new scientific questions and to form testable hypotheses.
We also collaborate with other international research groups and provide them with data from cell culture experiments and other molecular analyses.
