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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 model...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2013
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720774/ https://www.ncbi.nlm.nih.gov/pubmed/23935862 http://dx.doi.org/10.1371/journal.pone.0068358 |