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BMCBI
2006
119views more  BMCBI 2006»
15 years 6 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
274
Voted
ICALP
2009
Springer
16 years 7 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty
DASFAA
2010
IEEE
419views Database» more  DASFAA 2010»
16 years 1 months ago
Incremental Clustering for Trajectories
Trajectory clustering has played a crucial role in data analysis since it reveals underlying trends of moving objects. Due to their sequential nature, trajectory data are often rec...
Zhenhui Li, Jae-Gil Lee, Xiaolei Li, Jiawei Han
BMCBI
2008
143views more  BMCBI 2008»
15 years 6 months ago
Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering
Background: The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, ...
Shibu Yooseph, Weizhong Li, Granger G. Sutton
BMCBI
2006
134views more  BMCBI 2006»
15 years 6 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden