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BMCBI
2007

Difference-based clustering of short time-course microarray data with replicates

8 years 9 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically. Results: We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods. Conclusions: Assessments using simu...
Jihoon Kim, Ju Han Kim
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2007
Where BMCBI
Authors Jihoon Kim, Ju Han Kim
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