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Molecules 2017, 22(12), 2228; https://doi.org/10.3390/molecules22122228

Multi-Objective Optimization Algorithm to Discover Condition-Specific Modules in Multiple Networks

1
School of Computer Science and Technology, Xidian University, Xi’an 710071, China
2
College of Information Engineering, Northwest Agriculture and Forestry University, Yangling, Xianyang 712100, China
*
Author to whom correspondence should be addressed.
Received: 27 October 2017 / Revised: 10 December 2017 / Accepted: 11 December 2017 / Published: 14 December 2017
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Abstract

The advances in biological technologies make it possible to generate data for multiple conditions simultaneously. Discovering the condition-specific modules in multiple networks has great merit in understanding the underlying molecular mechanisms of cells. The available algorithms transform the multiple networks into a single objective optimization problem, which is criticized for its low accuracy. To address this issue, a multi-objective genetic algorithm for condition-specific modules in multiple networks (MOGA-CSM) is developed to discover the condition-specific modules. By using the artificial networks, we demonstrate that the MOGA-CSM outperforms state-of-the-art methods in terms of accuracy. Furthermore, MOGA-CSM discovers stage-specific modules in breast cancer networks based on The Cancer Genome Atlas (TCGA) data, and these modules serve as biomarkers to predict stages of breast cancer. The proposed model and algorithm provide an effective way to analyze multiple networks. View Full-Text
Keywords: multiple networks; specific modules; multi-objective optimization; network analysis multiple networks; specific modules; multi-objective optimization; network analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Ma, X.; Sun, P.; Zhao, J. Multi-Objective Optimization Algorithm to Discover Condition-Specific Modules in Multiple Networks. Molecules 2017, 22, 2228.

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