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» A Repulsive Clustering Algorithm for Gene Expression Data
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BIBM
2008
IEEE
125views Bioinformatics» more  BIBM 2008»
13 years 7 months ago
Systems Biology via Redescription and Ontologies (III): Protein Classification Using Malaria Parasite's Temporal Transcriptomic
This paper addresses the protein classification problem, and explores how its accuracy can be improved by using information from time-course gene expression data. The methods are ...
Antonina Mitrofanova, Samantha Kleinberg, Jane Car...
BIOINFORMATICS
2010
109views more  BIOINFORMATICS 2010»
13 years 7 months ago
Phylogenetic networks do not need to be complex: using fewer reticulations to represent conflicting clusters
Phylogenetic trees are widely used to display estimates of how groups of species evolved. Each phylogenetic tree can be seen as a collection of clusters, subgroups of the species ...
Leo van Iersel, Steven Kelk, Regula Rupp, Daniel H...
BMCBI
2006
146views more  BMCBI 2006»
13 years 7 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
BMCBI
2005
119views more  BMCBI 2005»
13 years 7 months ago
Proceedings of the Second Annual Conference of the MidSouth Computational Biology and Bioinformatics Society
The MCBIOS 2004 conference brought together regional researchers and students in biology, computer science and bioinformatics on October 7th-9th 2004 to present their latest work....
Jonathan D. Wren, William Slikker Jr.
ICPR
2008
IEEE
14 years 9 months ago
Active query selection for semi-supervised clustering
Semi-supervised clustering allows a user to specify available prior knowledge about the data to improve the clustering performance. A common way to express this information is in ...
Anil K. Jain, Pavan Kumar Mallapragada, Rong Jin