The Flag-based Algorithm - International Journal of Computers

Proteins and the networks they determine, called interactome net- works, have received attention at an important degree during the last years, because they have been discovered to have an influence on some complex bi- ological phenomena, such as problematic disorders like cancer. This paper presents a contribution that aims to optimize the detection of protein commu- nities

through a greedy algorithm that is implemented in the C programming language. The optimization involves a double improvement in relation to pro- tein 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 se- quential community detection approaches, and also to the sequential algorithm of Newman and Girvan. Keywords: Interactome networks, protein-protein interactions, protein com- munities, cancer, greedy algorithm. 1 Introduction 1.1 Basic Considerations on Protein Networks and Their Importance Interactome networks, or, more specifically, networks of proteins, determine a fundamen- tal biological theoretical entity. Theoretical and practical endeavours often use interactome networks-related formalisms in order to analyze the protein interactions that determine a biolog- ical network, which is essential for the proper organization and function of a biological organism. These networks exhibit a complex structure, which implies that any research activity in the field is handled with inherent theoretical and technical difficulties. Nevertheless, the dynamics and the structure of these biological networks have to be accurately understood, as they play an important role on the function of a biological organism seen as a whole, regardless their degree of structural complexity. As a consequence, it is highly required to design and implement efficient proteomic data analysis techniques that can be integrated in any research framework that study the structure and properties of the interactome networks. Copyright c© 2006-2011 by CCC Publications 34 R. Bocu, S. Tabirca The aim of this paper is to present a novel and faster algorithm that performs the detection of communities in the interactome networks, based on a computationally-effective greedy technique. The significant influence that proteins exercise on fundamental physiological processes has been demonstrated in a series of recent contributions. In this respect, this paper re-states our research’s previous developments, apart from the algorithmic optimization itself, that cancer affects the most important proteins in the interactome network and, as a consequence, the normal function of the organism is greatly disturbed....

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