RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Download

index.pdf

Date

2009-09-09

Author

MACROPOL, Kathy
Can, Tolga
Singh, Ambuj K.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

180
views

90
downloads

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.

Subject Keywords

Complexes, Algorithms, Modules

URI

https://hdl.handle.net/11511/47692

Journal

BMC BIOINFORMATICS

DOI

https://doi.org/10.1186/1471-2105-10-283

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Rigorous optimizations of three dimensional antenna arrays using full wave simulations Onol, Can; Gokce, Ozer; Boyacı, Huseyın; Ergül, Özgür Salih (null; 2015-07-09) We present optimizations of three-dimensional antenna arrays using heuristic techniques coupled with the multilevel fast multipole algorithm (MLFMA). Without resorting to any periodicity and infinity assumptions, antenna arrays are modeled with surface integral equations and simulated via MLFMA, which also enables the analysis of arrays with non-identical elements. Genetic algorithms and particle swarm optimization methods are employed on the complex data produced by MLFMA in phasor domain to find optimal s...
PARALLEL MULTILEVEL FAST MULTIPOLE ALGORITHM FOR COMPLEX PLASMONIC METAMATERIAL STRUCTURES Ergül, Özgür Salih (2013-11-09) A parallel implementation of the multilevel fast multipole algorithm (MLFMA) is developed for fast and accurate solutions of electromagnetics problems involving complex plasmonic metamaterial structures. Composite objects that consist of multiple penetrable regions, such as dielectric, lossy, and plasmonic parts, are formulated rigorously with surface integral equations and solved iteratively via MLFMA. Using the hierarchical strategy for the parallelization, the developed implementation is capable of simul...
Rigorous Solutions of Large-Scale Scattering Problems Discretized with Hundreds of Millions of Unknowns Guerel, L.; Ergül, Özgür Salih (2009-09-18) We present fast and accurate solutions of large-scale scattering problems using a parallel implementation of the multilevel fast multipole algorithm (MLFMA). By employing a hierarchical partitioning strategy, MLFMA can be parallelized efficiently on distributed-memory architectures. This way, it becomes possible to solve very large problems discretized with hundreds of millions of unknowns. Effectiveness of the developed simulation environment is demonstrated on various scattering problems involving canonic...
Nested Iterative Solutions of Electromagnetic Problems Using Approximate Forms of the Multilevel Fast Multipole Algorithm Onol, Can; Ucuncu, Arif; Karaosmanoglu, Bariscan; Ergül, Özgür Salih (2017-03-24) Nested iterative solutions using full and approximate forms of the multilevel fast multipole algorithm (MLFMA) are presented for efficient analysis of electromagnetic problems. The developed mechanism is based on preconditioning an iterative solution via another iterative solution, and this way, nesting multiple solutions as layers. The accuracy is systematically reduced from top to bottom by using the on-the-fly characteristics of MLFMA, as well as the iterative residual errors. As a demonstration, a three...
PARALLEL IMPLEMENTATION OF MLFMA FOR HOMOGENEOUS OBJECTS WITH VARIOUS MATERIAL PROPERTIES Ergül, Özgür Salih (2011-01-01) We present a parallel implementation of the multilevel fast multipole algorithm (MLFMA) for fast and accurate solutions of electromagnetics problems involving homogeneous objects with diverse material properties. Problems are formulated rigorously with the electric and magnetic current combined-field integral equation (JMCFIE) and solved iteratively using MLFMA parallelized with the hierarchical partitioning strategy. Accuracy and efficiency of the resulting implementation are demonstrated on canonical prob...

Citation Formats

K. MACROPOL, T. Can, and A. K. Singh, “RRW: repeated random walks on genome-scale protein networks for local cluster discovery,” BMC BIOINFORMATICS, pp. 0–0, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47692.