Altuntaş, VolkanGok, Murat2021-03-202021-03-202017978-1-5386-0930-9https://hdl.handle.net/20.500.12885/9862017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEYRecent studies of biological networks show that these networks arc robust against the random or selective deletion of network nodes and I or edges. Ability to maintain performance of network under mutations is a key feature of live systems that has long been recognized. However, the molecular and cellular basis of this stability has just begun to be understood. Robustness is a key to understanding cellular complexity, illuminating design principles, and encouraging closer interaction between experiment and theory. A biological network mutation can be defined as the creation of a new network with k allowed network change operations for a given G network. While mutating the network, our goal is to observe the change in the measured distance estimate value after k changes of the defined distance measurement method M. In this study, the effects of edge deletion and edge insertion mutations on network topology and diffusion-based function estimation algorithms are investigated by using random mutation model on the protein-protein interaction network of eukaryote Saccharomyces cerevisiae yeast, containing 5936 nodes and 65139 edges. Experimental results shows that Saccharomyces cerevisiae protein-protein interaction network has high robustness against random mutations and that the generated mutations have no significant effect on network topology and estimation techniques.trinfo:eu-repo/semantics/closedAccessbiological networkssaccharomyces cerevisiaenetwork mutationsConference Object116118WOS:000426856900022N/AN/A