Parallel SPICi

Hashemikhabir, Seyedsasan
Can, Tolga
In this paper, a concurrent implementation of the SPICi algorithm is proposed for clustering large-scale protein-protein interaction networks. This method is motivated by selecting a defined number of protein seed pairs and expanding multiple clusters concurrently using the selected pairs in each run; and terminates when there is no more protein node to process. This approach can cluster large PPI networks with considerable performance gain in comparison with sequential SPICi algorithm. Experiments show that this parallel approach can achieve nearly three times faster clustering time on the STRING human dataset on a system with 4-core CPU while maintaining high clustering quality.


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Background: We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e. g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins.
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We propose an interactive preference-based evolutionary algorithm for the clustering problem. The problem is highly combinatorial and referred to as NP-Hard in the literature. The goal of the problem is putting similar items in the same cluster and dissimilar items into different clusters according to a certain similarity measure, while maintaining some internal objectives such as compactness, connectivity or spatial separation. However, using one of these objectives is often not sufficient to detect differ...
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Deterministic modeling approach is the traditional way of analyzing the dynamical behavior of a reaction network. However, this approach ignores the discrete and stochastic nature of biochemical processes. In this study, modeling approaches, stochastic simulation algorithms and their relationships to each other are investigated. Then, stochastic and deterministic modeling approaches are applied to biological systems, Lotka-Volterra prey-predator model, Michaelis-Menten enzyme kinetics and JACK-STAT signalin...
Citation Formats
S. Hashemikhabir and T. Can, “Parallel SPICi,” 2011, Accessed: 00, 2020. [Online]. Available: