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BMCBI
2011
12 years 11 months ago
Gene set analysis for longitudinal gene expression data
Background: Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. ...
Ke Zhang, Haiyan Wang, Arne C. Bathke, Solomon W. ...
KES
2008
Springer
13 years 8 months ago
An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data
The validation of clusters discovered in bio-molecular data is a central issue in bioinformatics. Recently, stability-based methods have been successfully applied to the analysis o...
Roberto Avogadri, Matteo Brioschi, Francesca Ruffi...
BMCBI
2007
140views more  BMCBI 2007»
13 years 8 months ago
Evaluation of high-throughput functional categorization of human disease genes
Background: Biological data that are well-organized by an ontology, such as Gene Ontology, enables high-throughput availability of the semantic web. It can also be used to facilit...
James L. Chen, Yang Liu, Lee T. Sam, Jianrong Li, ...
BMCBI
2006
164views more  BMCBI 2006»
13 years 8 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 11 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...