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Author  |
Ruz, G.A.; Zuniga, A.; Goles, E. |

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Title |
A Boolean network model of bacterial quorum-sensing systems |
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Year |
2018 |
Publication |
International Journal Of Data Mining And Bioinformatics |
Abbreviated Journal |
Int. J. Data Min. Bioinform. |
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Volume |
21 |
Issue |
2 |
Pages |
123-144 |
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Keywords |
gene regulatory networks; quorum-sensing systems; Boolean networks; neural networks; network inference |
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Abstract |
There are several mathematical models to represent gene regulatory networks, one of the simplest is the Boolean network paradigm. In this paper, we reconstruct a regulatory network of bacterial quorum-sensing systems, in particular, we consider Paraburkholderia phytofirmans PsJN which is a plant growth promoting bacteria that produces positive effects in horticultural crops like tomato, potato and grape. To learn the regulatory network from temporal expression pattern of quorum-sensing genes at root plants, we present a methodology that considers the training of perceptrons for each gene and then the integration into one Boolean regulatory network. Using the proposed approach, we were able to infer a regulatory network model whose topology and dynamic exhibited was helpful to gain insight on the quorum-sensing systems regulation mechanism. We compared our results with REVEAL and Best-Fit extension algorithm, showing that the proposed neural network approach obtained a more biologically meaningful network and dynamics, demonstrating the effectiveness of the proposed method. |
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Address |
[Ruz, Gonzalo A.; Zuniga, Ana; Goles, Eric] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Av Diagonal Torres 2640, Santiago, Chile, Email: gonzalo.ruz@uai.cl; |
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Publisher |
Inderscience Enterprises Ltd |
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Language |
English |
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ISSN |
1748-5673 |
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Notes |
WOS:000451832900003 |
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Call Number |
UAI @ eduardo.moreno @ |
Serial |
933 |
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