DNA inside the nuclei of cells is folded into an intricate three-dimensional (3D) structure that influences how and when genes are turned on and off. For example, 3D interactions between distal regulatory elements, such as enhancers and their promoter targets are known to be responsible for regulating a range of genes with cell-type specific functions. Recent technologies coupling chromosome conformation capture to next-generation sequencing, such as Hi-C and ChIA-PET, allow for genome-wide identification of 3D interactions at unprecedented resolution. However, analysis is challenging due to the complexity of the data. This PhD-thesis presents several statistical models and computational tools to analyze such data, based on realistic assumptions regarding the underlying properties of chromatin structure. The thesis presents a model for analysis of 3D co-localization of selected elements in the genome. Additionally, the thesis presents a web-based analysis server called HiBrowse (https://hyperbrowser.uio.no/3d/), for performing statistical analysis of 3D genomes in a range of different settings. Finally, the thesis presents a statistical model for ChIA-PET data, allowing for accurate identification of significant interactions between regulatory regions in the genome.