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» Evaluation of clustering algorithms for gene expression data
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FLAIRS
2007
15 years 9 months ago
Improving Cluster Method Quality by Validity Indices
Clustering attempts to discover significant groups present in a data set. It is an unsupervised process. It is difficult to define when a clustering result is acceptable. Thus,...
Narjes Hachani, Habib Ounelli
ICAI
2004
15 years 8 months ago
K-medoid-style Clustering Algorithms for Supervised Summary Generation
This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
Nidal M. Zeidat, Christoph F. Eick

Publication
197views
14 years 2 months ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...
BMCBI
2007
168views more  BMCBI 2007»
15 years 6 months ago
Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks
Background: Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data ...
Nikolai Daraselia, Anton Yuryev, Sergei Egorov, Il...
BMCBI
2007
104views more  BMCBI 2007»
15 years 6 months ago
Comparative evaluation of gene-set analysis methods
Background: Multiple data-analytic methods have been proposed for evaluating gene-expression levels in specific biological pathways, assessing differential expression associated w...
Qi Liu, Irina Dinu, Adeniyi J. Adewale, John D. Po...