|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 10 van 11 gevonden artikelen
| Titel: |
Simulations of Simple Artificial Genetic Networks Reveal Features in the Use of Relevance Networks |
| Auteur: |
Angelica Lindlöf Zelmina Lubovac |
| Verschenen in: |
In silico biology |
| Paginering: | Jaargang 5 (2005) nr. 3 pagina's 239-249 |
| Jaar: |
2005-08-04 |
| Inhoud: |
Recent research on large scale microarray analysis has explored the use of Relevance Networks to find networks of genes that are associated to each other in gene expression data. In this work, we compare Relevance Networks with other types of clustering methods to test some of the stated advantages of this method. The dataset we used consists of artificial time series of Boolean gene expression values, with the aim of mimicking microarray data, generated from simple artificial genetic networks. By using this dataset, we could not confirm that Relevance Networks based on mutual information perform better than Relevance Networks based on Pearson correlation, partitional clustering or hierarchical clustering, since the results from all methods were very similar. However, all three methods successfully revealed the subsets of co-expressed genes, which is a valuable step in identifying co-regulation. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 10 van 11 gevonden artikelen
| << vorige | volgende >> |