We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust clustering under an ...
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
Background: Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However...
Tung T. Nguyen, Richard R. Almon, Debra C. DuBois,...