541 search results - page 26 / 109 » Incorporating Gene Ontology in Clustering Gene Expression Da... |
BMCBI
2008
13 years 8 months ago
2008
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
BMCBI
2002
13 years 8 months ago
2002
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
RECOMB
2007
Springer
14 years 8 months ago
2007
Springer
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
BMCBI
2006
13 years 8 months ago
2006
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
BMCBI
2006
13 years 8 months ago
2006
Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...