Sciweavers

128 search results - page 3 / 26
» Visualization and analysis of microarray and gene ontology d...
Sort
View
BMCBI
2006
183views more  BMCBI 2006»
13 years 4 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
AIME
2007
Springer
13 years 11 months ago
Interpreting Gene Expression Data by Searching for Enriched Gene Sets
This paper presents a novel method integrating gene-gene interaction information and Gene Ontology for the construction of new gene sets that are potentially enriched. Enrichment o...
Igor Trajkovski, Nada Lavrac
BMCBI
2008
137views more  BMCBI 2008»
13 years 4 months ago
VennMaster: Area-proportional Euler diagrams for functional GO analysis of microarrays
Background: Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) datab...
Hans A. Kestler, André Müller, Johann ...
BMCBI
2010
161views more  BMCBI 2010»
13 years 4 months ago
GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms
Background: An important objective of DNA microarray-based gene expression experimentation is determining interrelationships that exist between differentially expressed genes and ...
Saurin D. Jani, Gary L. Argraves, Jeremy L. Barth,...
JBI
2008
159views Bioinformatics» more  JBI 2008»
13 years 4 months ago
SEGS: Search for enriched gene sets in microarray data
Gene Ontology (GO) terms are often used to interpret the results of microarray experiments. The most common approach is to perform Fisher's exact tests to find gene sets anno...
Igor Trajkovski, Nada Lavrac, Jakub Tolar