Computational Biology of Gene Transcriptional Regulation

Gene expression is the bridge between genetic information to biological function. Development of biotechnologies has enabled comprehensive profiling of gene expression, especially at the level of transcriptional regulation. The huge scale of data generated has reformed the way of biological studies and computational biology, or bioinformatics, analysis has become crucial. In this dissertation, I summarize three discoveries enabled by computational biology approaches. In the first project, I collaborated with experimental biologists and reported a previously unknown connection between enhancer transcription and gene regulation. In the second project, I proposed a novel analysis methodology that identified enhancer transcripts as targets to modulate gene expression. In the third project, I applied machine learning techniques that efficiently identified key cell types from heterogeneous samples by transcriptome profiling.