Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data

This conference paper was presented in the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013; New York, NY; United States; 16 July 2013 through 18 July 2013 [© 2013 IEEE] The conference paper's definite version is available at: http://dx.doi.org/1...

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Main Authors:	Showkat, Dilruba, Kabir, Mitra Lutful
Other Authors:	Department of Computer Science and Engineering, BRAC University
Format:	Conference paper
Language:	English
Published:	© 2013 IEEE 2016
Subjects:	Gene regulatory networks Inference methods Objective functions Optimal solutions
Online Access:	http://hdl.handle.net/10361/7341 http://dx.doi.org/10.1109/ICCI-CC.2013.6622244

id	10361-7341
record_format	dspace
spelling	10361-73412022-01-27T03:12:56Z Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data Showkat, Dilruba Kabir, Mitra Lutful Department of Computer Science and Engineering, BRAC University Gene regulatory networks Inference methods Objective functions Optimal solutions This conference paper was presented in the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCICC 2013; New York, NY; United States; 16 July 2013 through 18 July 2013 [© 2013 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/ICCI-CC.2013.6622244 Multi-objective optimization plays a significant role in optimizing many real life problems, where we desire to optimize more than one objective. Numerous multi-objective optimization algorithm exists in research. NSGA-II and SPEA2 are widely used multi-objective optimization algorithms. SPEA2+ algorithm performs better than the other multi-objective optimization algorithms in terms of searching and maintaining diversity in the optimal solution. In this research, to reconstruct the gene regulatory network we have proposed a new Hybrid SPEA2+ algorithm based inference method. We have proposed a new objective function to obtain sparse gene network structure more precisely. To reverse engineer the gene regulatory network we have used linear time variant model. The proposed approach is at first tested against synthetic noise free time series datasets. It has successfully inferred all the correct regulations from noise free time series datasets. Then it was applied on synthetic noisy time series datasets. Even with the presence of noise, the proposed method have correctly captured all the correct gene regulations successfully. The proposed reconstruction method has been further validated by analyzing the real gene expression datasets of SOS DNA repair system in Escherichia coli. Our proposed method have shown its potency in finding more correct regulations and this has been confirmed by comparing the obtained gene regulations with the results of other existing researches. Published 2016-12-26T09:15:02Z 2016-12-26T09:15:02Z 2013-07 Conference paper Showkat, D., & Kabir, M. (2013). Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data. Paper presented at the Proceedings of the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCICC 2013, 195-202. doi:10.1109/ICCI-CC.2013.6622244 9.78148E+12 http://hdl.handle.net/10361/7341 http://dx.doi.org/10.1109/ICCI-CC.2013.6622244 en http://ieeexplore.ieee.org/document/6622244/ © 2013 IEEE
institution	Brac University
collection	Institutional Repository
language	English
topic	Gene regulatory networks Inference methods Objective functions Optimal solutions
spellingShingle	Gene regulatory networks Inference methods Objective functions Optimal solutions Showkat, Dilruba Kabir, Mitra Lutful Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
description	This conference paper was presented in the 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2013; New York, NY; United States; 16 July 2013 through 18 July 2013 [© 2013 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/ICCI-CC.2013.6622244
author2	Department of Computer Science and Engineering, BRAC University
author_facet	Department of Computer Science and Engineering, BRAC University Showkat, Dilruba Kabir, Mitra Lutful
format	Conference paper
author	Showkat, Dilruba Kabir, Mitra Lutful
author_sort	Showkat, Dilruba
title	Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
title_short	Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
title_full	Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
title_fullStr	Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
title_full_unstemmed	Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data
title_sort	inference of genetic networks using multi-objective hybrid spea2+ from microarray data
publisher	© 2013 IEEE
publishDate	2016
url	http://hdl.handle.net/10361/7341 http://dx.doi.org/10.1109/ICCI-CC.2013.6622244
work_keys_str_mv	AT showkatdilruba inferenceofgeneticnetworksusingmultiobjectivehybridspea2frommicroarraydata AT kabirmitralutful inferenceofgeneticnetworksusingmultiobjectivehybridspea2frommicroarraydata
_version_	1814309406580408320

Inference of genetic networks using multi-objective hybrid SPEA2+ from microarray data

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