Published June 20, 2016
| Version v1
Publication
Unravelling the Yeast Cell Cycle Using the TriGen Algorithm
Description
Analyzing microarray data represents a computational challenge
due to the characteristics of these data. Clustering techniques are
widely applied to create groups of genes that exhibit a similar behavior
under the conditions tested. Biclustering emerges as an improvement of
classical clustering since it relaxes the constraints for grouping allowing
genes to be evaluated only under a subset of the conditions and not under
all of them. However, this technique is not appropriate for the analysis of
temporal microarray data in which the genes are evaluated under certain
conditions at several time points. In this paper, we present the results of
applying the TriGen algorithm, a genetic algorithm that finds triclusters
that take into account the experimental conditions and the time points,
to the yeast cell cycle problem, where the goal is to identify all genes
whose expression levels are regulated by the cell cycle.
Additional details
Identifiers
- URL
- https://idus.us.es/handle/11441/42455
- URN
- urn:oai:idus.us.es:11441/42455