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.


RRW: repeated random walks on genome-scale protein networks for local cluster discovery
MACROPOL, Kathy; Can, Tolga; Singh, Ambuj K. (2009-09-09)
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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Cetinkaya, N; Urkmez, A; Erkmen, İsmet; Yalcinoz, T (2005-01-01)
This paper presents a new algorithm and computation approach to solve the economic load dispatch (ELD) in electrical power systems. We applied a new power formula to solve the LLD problem. If production units cost Curves are represented property then ELD becomes More Correct. In this respect we assumed that production units have prohibited operating zones. Cost curves of the production units are generally accepted as piece-wise quadratic function. The power production is cheaper since we do not use the prod...
Representing temporal knowledge in connectionist expert systems
Alpaslan, Ferda Nur (1996-09-27)
This paper introduces a new temporal neural networks model which can be used in connectionist expert systems. Also, a Variation of backpropagation algorithm, called the temporal feedforward backpropagation algorithm is introduced as a method for training the neural network. The algorithm was tested using training examples extracted from a medical expert system. A series of experiments were carried out using the temporal model and the temporal backpropagation algorithm. The experiments indicated that the alg...
An interactive preference based multiobjective evolutionary algorithm for the clustering problem
Demirtaş, Kerem; Özdemirel, Nur Evin; Karasakal, Esra; Department of Industrial Engineering (2011)
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...
Direction of arrival estimation algorithm with uniform linear and circular array
Caylar, Selcuk; Leblebicioğlu, Mehmet Kemal; Dural, Guelbin (2007-01-01)
In this paper mutual coupling effects on Modified Neural Multiple Source Tracking Algorithm (MN-MUST) has been studied. MN-MUST algorithm applied to the Uniform Circular Array (UCA) geometry for the first time. The validity of MN-MUST algorithm in the presence of mutual coupling has been proved for both Uniform Linear Array (ULA) and UCA. Simulation results of MN-MUST algorithm are provided for UCA for the first time. The presence of mutual coupling degraded the MN-MUST algorithm performed in the absence of...
Citation Formats
S. Hashemikhabir and T. Can, “Parallel SPICi,” 2011, Accessed: 00, 2020. [Online]. Available: