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» A Repulsive Clustering Algorithm for Gene Expression Data
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BMCBI
2005
189views more  BMCBI 2005»
13 years 9 months ago
Quantitative inference of dynamic regulatory pathways via microarray data
Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway ar...
Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen
BMCBI
2002
136views more  BMCBI 2002»
13 years 8 months ago
Making sense of EST sequences by CLOBBing them
Background: Expressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed g...
John Parkinson, David B. Guiliano, Mark L. Blaxter
DMKD
2003
ACM
96views Data Mining» more  DMKD 2003»
14 years 2 months ago
Using transposition for pattern discovery from microarray data
We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated. Such matrices provide expression values for given biol...
François Rioult, Jean-François Bouli...
BMCBI
2011
13 years 4 months ago
RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis
Background: The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such...
Barry Zeeberg, Hongfang Liu, Ari B. Kahn, Martin E...
GECCO
2005
Springer
146views Optimization» more  GECCO 2005»
14 years 2 months ago
An empirical study of the robustness of two module clustering fitness functions
Two of the attractions of search-based software engineering (SBSE) derive from the nature of the fitness functions used to guide the search. These have proved to be highly robust...
Mark Harman, Stephen Swift, Kiarash Mahdavi