Analysis of Genome-Scale Data

Abstract

The genetic material of every cell in an organism is stored inside DNA in the form of genes, which together form the genome. The information stored in the DNA is translated to RNA and subsequently to proteins, which form complex biological systems. The availability of whole genome sequences has given rise to the parallel development of other high-throughput approaches such as determining mRNA expression level changes, gene-deletion phenotypes, chromosomal location of DNA binding proteins, cellular location of proteins and protein-protein interactions. Many challenges are encountered when analyzing such data for biological or biomedical purposes. The work described in this thesis offers a number of improvements and/or suggestions in terms of data management, data preprocessing, integration of different types of genome-scale data, prioritization of hypotheses and improvement of existing annotation. As a result, the general usability, efficiency and precision increases for these types of data and can therefore be used more effectively, for instance to decipher complex biological systems, to identify possible drug targets or to aid gene function prediction.