Biological Network-based Approaches to The Functional Analysis of miRNAs in Prostate Cancer
| atmire.migration.oldid | 1453 | |
| dc.contributor.advisor | Alhajj, Reda | |
| dc.contributor.author | Alshalalfa, Mohammed | |
| dc.date.accessioned | 2013-09-25T22:07:25Z | |
| dc.date.available | 2013-11-12T08:00:18Z | |
| dc.date.issued | 2013-09-25 | |
| dc.date.submitted | 2013 | en |
| dc.description.abstract | The cell is a highly organized system of interacting molecules that operate together in a complex and efficient manner to achieve biological functions and cellular phenotypes. Traditional biology studied these components one at a time, yielding limited insights about the way a cell functions. It is now apparent that the most effective way to understand how the cell works is to unravel how these different components work together. Recent advances in biological research have led to an explosive growth in scientific data to study and characterize the function of the different components of the cell. Thanks to high-throughput techniques, an explosive growth in the size and type of biological information are generated to reveal the internal complexity of cells. This has lead to a rapid increase in the number of computational techniques developed to mine the data and reveal functional understandings of the cell. Deciphering the molecular interactions among the cellular molecules embodies a more comprehensive view of the cellular function, and integrating heterogenous interaction networks and expression data reveals a system-level understanding of the cell behavior. This thesis focuses on integrating multiple heterogenous biological networks, in particular protein networks and miRNA-target interactions, to facilitate miRNA research. This integration layer between miRNAs and protein networks helps to study the propagation of miRNAs’ influence through the biological networks of the targets. This thesis provides a profound review of the cross-talk between miRNAs and biological networks, particularly protein networks. The role of miRNAs as part of the cellular system and their influence on functional protein modules is characterized in prostate cancer progression. In this thesis, different approaches are proposed to analyze the integration layer and provide potential applications to the genomic studies of miRNAs. The first approach predicts miRNAs with high influence on protein networks and assesses their prognostic significance. The second approach predicts protein complexes that are influences by miRNAs during prostate progression. The third approach characterizes the modulation effect of genes that encode protein partners of the protein encoded by miRNA targets. The fourth approach uses protein networks to identify miRNAs enriched in gene lists. The proposed methods reveal that integrating miRNA-target and protein networks provides a new layer of biological information that assists to reveal miRNA-target modules with potential function, and uncover principles governing miRNA-mediated regulation of targets in biological networks. The results suggest that the proposed methods are promising to reveal miRNA-mediated regulation, in the context of protein networks, involved in prostate cancer progression. This thesis shows that integrating protein networks and miRNA-target networks is a valuable source of knowledge that help researchers understand how miRNA exert their function on the cellular system. This facilitates miRNA genomic research to identify miRNAs with strong influence on the proteins regulating the cell function, and thus gain better characterization of their role in disease progression and possible utility for therapeutic purposes. | en_US |
| dc.identifier.citation | Alshalalfa, M. (2013). Biological Network-based Approaches to The Functional Analysis of miRNAs in Prostate Cancer (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25127 | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/25127 | |
| dc.identifier.uri | http://hdl.handle.net/11023/1053 | |
| dc.language.iso | eng | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.institution | University of Calgary | en |
| dc.publisher.place | Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | Bioinformatics | |
| dc.subject.classification | Integrative biology | en_US |
| dc.subject.classification | Systems biology | en_US |
| dc.subject.classification | Biomarkers | en_US |
| dc.subject.classification | gene networks | en_US |
| dc.subject.classification | matrix decomposition | en_US |
| dc.subject.classification | regression analysis | en_US |
| dc.subject.classification | Gene expression | en_US |
| dc.subject.classification | protein interactions, | en_US |
| dc.subject.classification | microRNA | en_US |
| dc.subject.classification | Entropy | en_US |
| dc.subject.classification | gene modulation | en_US |
| dc.title | Biological Network-based Approaches to The Functional Analysis of miRNAs in Prostate Cancer | |
| dc.type | doctoral thesis | |
| thesis.degree.discipline | Computer Science | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Doctor of Philosophy (PhD) | |
| ucalgary.item.requestcopy | true |