Computational methods for analysing the regulation of genetic systems across species

Gene regulation in humans and other mammalian organisms is complex with many different layers. Despite huge advances in biomedical research, our ability to build a comprehensive and predictive model of gene regulation is still limited. There are increasing amounts of public genome-wide data available, containing a wealth of untapped knowledge about different aspects of gene regulation from across the tree of life. The main challenge and bottleneck is integrating and analysing this data to extract insights about gene regulation.In this thesis, I discuss the challenges pertaining to integrating data of different types,and from different species, to better understand gene regulation. Furthermore, I present a series of novel concepts, bioinformatics methods, software tools and case studies to address and overcome some of these issues.The key contributions of this thesis are:1. Investigation and method development for constructing and analysing mammalian gene regulatory networks2. Approaches and tools for large scale systems integration of public data and knowledge3. Investigation of issues and new methods for cross-species gene set analysis.