Year: 2011
Type: dissertation
Abstract: Centrality analysis has become an important part of biological network studies, notably\nthat of protein-protein interaction networks. It has long been known that the importance\nof a protein is determined by its connections and relationships to other proteins.\nIn the current work we look into centrality in other kinds of networks as well, notably\nthose based on gene expression data and drug effects on cancer cell lines. The purpose\nof this project is to show that centrality is useful for the analysis of several different\nkinds of biological networks. Firstly, we show that the most central genes in the p53\nprotein interaction network are also the most relevant regarding the network’s ability\nto suppress tumors. Secondly, we look into different types of breast cancer and demonstrate\nthat central genes are among the best discriminators between different classes of\ndata. It is also interesting to see many of the p53 pathway elements coming up among\nthe top central genes. Finally, we apply centrality on cancer treatment data and show\nhow it can be used to identify good drug candidates for different kinds of cancer.\n
Author: Triinu Tasa
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W376580281