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» Scalable Rule-Based Gene Expression Data Classification
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CSB
2004
IEEE
164views Bioinformatics» more  CSB 2004»
15 years 3 months ago
Biclustering in Gene Expression Data by Tendency
The advent of DNA microarray technologies has revolutionized the experimental study of gene expression. Clustering is the most popular approach of analyzing gene expression data a...
Jinze Liu, Jiong Yang, Wei Wang 0010
SIGMOD
2005
ACM
161views Database» more  SIGMOD 2005»
15 years 11 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
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
15 years 3 months ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li
ISMDA
2005
Springer
15 years 5 months ago
Relevance, Redundancy and Differential Prioritization in Feature Selection for Multiclass Gene Expression Data
The large number of genes in microarray data makes feature selection techniques more crucial than ever. From various ranking-based filter procedures to classifier-based wrapper tec...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng
BMCBI
2007
207views more  BMCBI 2007»
14 years 11 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...