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» Combining microarrays and genetic analysis
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BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
14 years 4 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
BIRD
2007
Springer
118views Bioinformatics» more  BIRD 2007»
14 years 1 months ago
Biological Network Inference Using Redundancy Analysis
The paper presents MRNet, an original method for inferring genetic networks from microarray data. This method is based on maximum relevance/minimum redundancy (MRMR), an effective ...
Patrick Emmanuel Meyer, Kevin Kontos, Gianluca Bon...
BMCBI
2010
136views more  BMCBI 2010»
13 years 10 months ago
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, producti...
Yevhen Vainshtein, Mayka Sanchez, Alvis Brazma, Ma...
DILS
2005
Springer
14 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
BMCBI
2007
148views more  BMCBI 2007»
13 years 9 months ago
p53FamTaG: a database resource of human p53, p63 and p73 direct target genes combining in silico prediction and microarray data
Background: The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis a...
Elisabetta Sbisà, Domenico Catalano, Giorgi...