The Flag-based Algorithm - A Novel Greedy Method that Optimizes Protein Communities Detection

Razvan Bocu, Sabin Tabirca


Proteins and the networks they determine, called interactome networks, have received attention at an important degree during the last years, because they have been discovered to have an influence on some complex biological phenomena, such as problematic disorders like cancer. This paper presents a contribution that aims to optimize the detection of protein communities through a greedy algorithm that is implemented in the C programming language. The optimization involves a double improvement in relation to protein communities detection, which is accomplished both at the algorithmic and programming level. The resulting implementation’s performance was carefully tested on real biological data and the results acknowledge the relevant speedup that the optimization determines. Moreover, the results are in line with the previous findings that our current research produced, as it reveals and confirms the existence of some important properties of those proteins that participate in the carcinogenesis process. Apart from being particularly useful for research purposes, the novel community detection algorithm also dramatically speeds up the proteomic databases analysis process, as compared to some other sequential community detection approaches, and also to the sequential algorithm of Newman and Girvan.


Interactome networks, protein-protein interactions, protein communities, cancer, greedy algorithm

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