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» Microarray Gene Expression Data Analysis
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BMCBI
2006
147views more  BMCBI 2006»
14 years 9 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2010
214views more  BMCBI 2010»
14 years 9 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BMCBI
2011
14 years 1 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
ICDE
2004
IEEE
133views Database» more  ICDE 2004»
15 years 11 months ago
GenExplore: Interactive Exploration of Gene Interactions from Microarray Data
DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liyin...
BMCBI
2008
204views more  BMCBI 2008»
14 years 9 months ago
EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarra
Background: Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotat...
Javier Forment, Francisco Gilabert Villamón...