Performance Evaluation of Some Clustering Algorithms and Validity Indices
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Clustering gene expression series with prior knowledge
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Clustering Time-Series Gene Expression Data with Unequal Time Intervals
Transactions on Computational Systems Biology X
| Hi-index | 0.00 |
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We also introduce a variant of a clustering index that can effectively decide upon the optimal number of clusters for a given dataset. The clustering method is based on a profile-alignment approach, which minimizes the mean-square-error of the first order differentials, to hierarchically cluster microarray time-series data. The effectiveness of our algorithm has been tested on datasets drawn from standard experiments, showing that our approach can effectively cluster the datasets based on profile similarity.