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» Algorithms for Finding Gene Clusters
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151
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BMCBI
2010
153views more  BMCBI 2010»
15 years 2 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
110
Voted
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 2 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
134
Voted
ICDM
2008
IEEE
122views Data Mining» more  ICDM 2008»
15 years 9 months ago
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
Chris H. Q. Ding, Tao Li, Michael I. Jordan
145
Voted
CSB
2003
IEEE
106views Bioinformatics» more  CSB 2003»
15 years 8 months ago
Reconstruction of Ancestral Gene Order after Segmental Duplication and Gene Loss
As gene order evolves through a variety of chromosomal rearrangements, conserved segments provide important insight into evolutionary relationships and functional roles of genes. ...
Jun Huan, Jan Prins, Wei Wang 0010, Todd J. Vision
ISNN
2004
Springer
15 years 8 months ago
A Novel Clustering Analysis Based on PCA and SOMs for Gene Expression Patterns
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...
Hong-Qiang Wang, De-Shuang Huang, Xing-Ming Zhao, ...