Abstract
The body consists of hundreds of di erent cell types as diverse as heart, blood, muscle and brain cells. All cells contain the same DNA which is the hereditary material that de nes who we are and how we look. In each cell parts of the DNA called genes are transcribed into RNA that is translated into proteins. All cells need di erent proteins in di erent amounts to function properly. The transcription and translation are therefore highly regulated and the regulation is not fully understood. It is important to learn as much as possible about both transcriptional and translational regulation to better understand and cure diseases. The focus of this thesis is transcriptional regulation. The main aim was to gain new insight into transcriptional regulation but a secondary goal was to develop new bioinformatic methods to facilitate future research.
Three di erent studies are presented each focusing on di erent aspects of transcriptional regulation. In the rst study we develop a machine learning framework to predict mRNA production, stalling and elongation of RNA polymerase II using publicly available histone modi cation data. The study reveals new pieces of information about the histone code. Besides that the framework is highly applicable to other types of genomic data and can be used in future research.
The second study is a thorough study of which factors that in uence the retention of transcription factors between human and mice. The explored factors are the two key transcription factors in adipogensis PPAR and C/EBP . The study reveals new information about the cooperation of the factors and the results indicate that other possible unknown factors are important as well. The study also resulted in a new method to measure retention of transcription factor binding sites.
The last study is a toxicological study of the impact of multiwalled carbon nanotubes to mice lungs. Besides gaining new insight into the e ects of nanotubes the data is also used to explore the role of alternative promoter usage and enhancers in response to external stimuli.
Three di erent studies are presented each focusing on di erent aspects of transcriptional regulation. In the rst study we develop a machine learning framework to predict mRNA production, stalling and elongation of RNA polymerase II using publicly available histone modi cation data. The study reveals new pieces of information about the histone code. Besides that the framework is highly applicable to other types of genomic data and can be used in future research.
The second study is a thorough study of which factors that in uence the retention of transcription factors between human and mice. The explored factors are the two key transcription factors in adipogensis PPAR and C/EBP . The study reveals new information about the cooperation of the factors and the results indicate that other possible unknown factors are important as well. The study also resulted in a new method to measure retention of transcription factor binding sites.
The last study is a toxicological study of the impact of multiwalled carbon nanotubes to mice lungs. Besides gaining new insight into the e ects of nanotubes the data is also used to explore the role of alternative promoter usage and enhancers in response to external stimuli.
| Originalsprog | Engelsk |
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| Forlag | Department of Biology, Faculty of Science, University of Copenhagen |
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| Status | Udgivet - 2014 |