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BIBE
2005
IEEE
9 years 8 months ago
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets
One of the major problems in biological data integration is that many data sources are stored as flat-files, with a variety of different layouts. Integrating data from such sour...
Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agra...
BMCBI
2008
160views more  BMCBI 2008»
9 years 2 months ago
Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'
Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cro...
Alexandre Kuhn, Ruth Luthi-Carter, Mauro Delorenzi
ENGL
2007
180views more  ENGL 2007»
9 years 2 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar
BMCBI
2006
183views more  BMCBI 2006»
9 years 2 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
10 years 2 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
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