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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2007
185views more  BMCBI 2007»
15 years 6 months ago
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, a...
André Fujita, João Ricardo Sato, Car...
BMCBI
2006
86views more  BMCBI 2006»
15 years 6 months ago
The impact of sample imbalance on identifying differentially expressed genes
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Kun Yang, Jianzhong Li, Hong Gao
159
Voted
ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
15 years 11 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010
ICTAI
2007
IEEE
16 years 13 days ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas
SIGMOD
2005
ACM
161views Database» more  SIGMOD 2005»
16 years 6 months ago
Mining Top-k Covering Rule Groups for Gene Expression Data
In this paper, we propose a novel algorithm to discover the topk covering rule groups for each row of gene expression profiles. Several experiments on real bioinformatics datasets...
Gao Cong, Kian-Lee Tan, Anthony K. H. Tung, Xin Xu