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RIVF
2008
14 years 11 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
DILS
2005
Springer
15 years 3 months ago
Integrating Heterogeneous Microarray Data Sources Using Correlation Signatures
Abstract. Microarrays are one of the latest breakthroughs in experimental molecular biology. Thousands of different research groups generate tens of thousands of microarray gene e...
Jaewoo Kang, Jiong Yang, Wanhong Xu, Pankaj Chopra
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
15 years 3 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
BMCBI
2006
203views more  BMCBI 2006»
14 years 9 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
BMCBI
2008
115views more  BMCBI 2008»
14 years 9 months ago
BioGraphE: high-performance bionetwork analysis using the Biological Graph Environment
Background: Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching h...
George Chin Jr., Daniel G. Chavarría-Mirand...