Računarske metode particionisanja i grupisanja u biološkim mrežama

Abstract

U ovoj disertaciji se istražuju aktuelni problemi bioinformatike i računarske biologije i metode za njihovo rješavanje...

In this dissertation some actual problems of bioinformatics and computational biology are explored, together with the methods for solving them. The following problems are considered: partitioning of sparse biological networks into k-plex subnetworks, prediction of the role of metabolites in metabolic reactions, partitioning of biological networks into highly connected components and the problem of identification of significant groups of proteins by adding new edges to the weighted protein interactions network. The aforementioned problems have theoretical importance in areas of machine learning and optimization, and practical application in biological research. In addition to solving the aforementioned problems from the computational aspect, the dissertation explores further application of the obtained results in the fields of biology and biochemistry, as well as the integration of results within existing bioinformatics tools. The problem of predicting the role of metabolites in metabolic reactions is solved by a predictive machine learning method based on the conditional random fields, while for the remaining three problems the algorithams based on variable neighbourhood search are developed. For solving the problem of identification of significant groups of proteins by adding new edges to the weighted protein interactions network, the variable neighbourhood search is only the first phase of the proposed solution, while in the second and the third phase of the proposed method, the integration with additional biological information and bioinformatics tools are performed. The proposed computational methods of partitioning and grouping in biological networks confirm existing findings in a new manner and lead to new discoveries about biological elements and the connections between them. By solving these problems and by interpreting the obtained results in this dissertation, a scientific contribution was made to the scientific field of computer science, particularly to the scientific disciplines of bioinformatics and computational biology.