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» Analysis techniques for microarray time-series data
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SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 10 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
BMCBI
2008
135views more  BMCBI 2008»
13 years 8 months ago
Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...
BMCBI
2010
136views more  BMCBI 2010»
13 years 8 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...
BMCBI
2006
94views more  BMCBI 2006»
13 years 8 months ago
Simulation of microarray data with realistic characteristics
Background: Microarray technologies have become common tools in biological research. As a result, a need for effective computational methods for data analysis has emerged. Numerou...
Matti Nykter, Tommi Aho, Miika Ahdesmäki, Pek...
BIOSYSTEMS
2007
115views more  BIOSYSTEMS 2007»
13 years 8 months ago
Evolving fuzzy rules to model gene expression
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Ricardo Linden, Amit Bhaya