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Title |
Computational methods for the Inference of Gene Regulatory Networks |
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Author |
Seema More, Accaamma V |
| Citation |
Vol. 11 No. 3 pp. 170-176 |
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Abstract |
In the last 10 years, Inference of Gene Regulatory Networks from Microarray data has become an important research area in Bioinformatics. Several algorithms have been proposed and Regulatory networks have been inferred with good accuracy for Saccromycin cervisea, Escherichia coli, Hela cells etc. A large amount of knowledge on various biological systems, e.g. gene regulation, metabolic regulations, and signal transduction are being continually accumulated over the years, though there remains a large portion that is not well understood. This paper is a survey of different techniques used for the inference of Gene regulatory networks. |
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Keywords |
Data mining, Bioinformatics, Gene Regulatory Network, Stochastic Model, Differential Equations, Association rule mining, Bayesian Network |
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