| Abstract [eng] |
This master’s thesis, ,,A MeSH-Term-Based Phenotype-Gene Association Dataset for Gene Prioritization” by Ariadna Šamatovič, was completed within the Systems Biology study program at Vilnius University. Understanding how genes are linked to diseases is essential for improving diagnosis and developing new treatments. However, identifying these relationships through experimental methods is time-consuming and expensive. Rapidly growing volume of biomedical literature makes manual extraction extremely difficult. This master’s thesis aims to develop a gene prioritization tool and structured database for identifying and storing disease-gene associations. A gene prioritization tool and structured dataset were created using information from PubMed, Gene2PubMed, and Gene Ontology (Gene2GO). The method focuses on identifying indirect relationships. This is done by connecting diseases to chemicals through MeSH terms, and then linking these chemicals to genes and their biological functions. These connections are quantified using a scoring system, and ranked based on their relevance to a selected disease. The developed system integrates multiple data sources into a unified pipeline. It also includes visualization features that illustrate the intermediate biological steps linking diseases to genes. Overall, this work provides an efficient and interpretable method for exploring disease-gene relationships. It has the potential to identify novel candidate genes and support future biomedical research. |
