Improved inference of gene regulatory networks through integrated Bayesian clustering and dynamic modeling of time-course expression data.
Inferring gene regulatory networks from expression data is difficult, but it is common and often useful. Most network problems are under-determined--there are more parameters than data points--and therefore data or parameter set reduction is often necessary. Correlation between variables in the mode...
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| Formato: | article |
| Lenguaje: | EN |
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Public Library of Science (PLoS)
2013
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| Acceso en línea: | https://doaj.org/article/9429b2263584432a9127019557ae603b |
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