| Record |
| Author |
Ruz, G.A.; Zuniga, A.; Goles, E. |
| Title |
A Boolean network model of bacterial quorum-sensing systems |
Type |
|
| Year |
2018 |
Publication |
International Journal Of Data Mining And Bioinformatics |
Abbreviated Journal |
Int. J. Data Min. Bioinform. |
| Volume |
21 |
Issue |
2 |
Pages |
123-144 |
| Keywords |
gene regulatory networks; quorum-sensing systems; Boolean networks; neural networks; network inference |
| 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. |
| 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; |
| Corporate Author |
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Thesis |
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| Publisher |
Inderscience Enterprises Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1748-5673 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000451832900003 |
Approved |
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| Call Number |
UAI @ eduardo.moreno @ |
Serial |
933 |
| Permanent link to this record |
