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» A Repulsive Clustering Algorithm for Gene Expression Data
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ICTAI
2007
IEEE
14 years 2 months 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»
14 years 7 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
BMCBI
2007
179views more  BMCBI 2007»
13 years 7 months ago
Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
Background: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset anno...
Hui Yu, Feng Wang, Kang Tu, Lu Xie, Yuan-Yuan Li, ...
JCB
2007
130views more  JCB 2007»
13 years 7 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
BICOB
2009
Springer
13 years 5 months ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...