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» Robust cross-race gene expression analysis
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BIBE
2007
IEEE
155views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Partial Mixture Model for Tight Clustering in Exploratory Gene Expression Analysis
Abstract—In this paper we demonstrate the inherent robustness of minimum distance estimator that makes it a potentially powerful tool for parameter estimation in gene expression ...
Yinyin Yuan, Chang-Tsun Li
BMCBI
2007
138views more  BMCBI 2007»
13 years 5 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
BMCBI
2006
148views more  BMCBI 2006»
13 years 5 months ago
Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of m
Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Mo...
Veronica Vinciotti, Xiaohui Liu, Rolf Turk, Emile ...
WCE
2007
13 years 6 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
13 years 11 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...