Background: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical m...
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...
Background: We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip ar...
Marina Bakay, Yi-Wen Chen, Rehannah H. A. Borup, P...
Background: Tiling array data is hard to interpret due to noise. The wavelet transformation is a widely used technique in signal processing for elucidating the true signal from no...
Alexander Karpikov, Joel S. Rozowsky, Mark Gerstei...