Computational Analysis of Transcriptional Regulation after Single and Multiple Drug Administration.
With the advances in transcriptomic analysis, the monitoring of genome-wide gene expression provides a powerful approach for determining the action of drugs. In this thesis, we analyzed the transcriptional responses of cells treated with drugs either alone or in combinations to explore their effects in two different applications: breast cancer therapy and cell conversion.
Overview
Abstract
Transcriptomics is the large-scale study of RNA molecules produced by the genome, in single cells or population of cells using high-throughput methods. With the advances in transcriptomic analysis, the monitoring of genome-wide gene expression provides a powerful approach for determining the action of drugs. In this thesis, we analyzed the transcriptional responses of cells treated with drugs either alone or in combinations to explore their effects in two different applications: breast cancer therapy and cell conversion.
Brief Biography
Trisevgeni Rapakoulia is a Ph.D. candidate in Xin Gao's group at King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia. She holds her Master's Degree in Informatics for Life Sciences, Medical School, University of Patras-Greece Specialization: Bioinformatics, 2013, and Bachelor's Degree in Computer Engineering & Informatics, University of Patras-Greece, 2010. Her research interests broadly concern Bioinformatics, Machine Learning, and Drug Combinations.
