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» Mining Spatial Gene Expression Data for Association Rules
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BMCBI
2008
167views more  BMCBI 2008»
14 years 11 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
BIBE
2007
IEEE
176views Bioinformatics» more  BIBE 2007»
15 years 6 months ago
HICCUP: Hierarchical Clustering Based Value Imputation using Heterogeneous Gene Expression Microarray Datasets
Abstract—A novel microarray value imputation method, HICCUP1 , is presented. HICCUP improves upon existing value imputation methods in the several ways. (1) By judiciously integr...
Qiankun Zhao, Prasenjit Mitra, Dongwon Lee, Jaewoo...
ICMCS
2008
IEEE
115views Multimedia» more  ICMCS 2008»
15 years 6 months ago
Spatial pyramid mining for logo detection in natural scenes
This work introduces a novel data mining scheme, spatial pyramid mining, to discover association rules at multiple resolutions in order to identify frequent spatial configuration...
Jim Kleban, Xing Xie, Wei-Ying Ma
BMCBI
2008
125views more  BMCBI 2008»
14 years 11 months ago
Exploration and visualization of gene expression with neuroanatomy in the adult mouse brain
Background: Spatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing effort...
Christopher Lau, Lydia Ng, Carol Thompson, Sayan D...
BMCBI
2011
14 years 3 months ago
SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data
Background: The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide r...
Xutao Deng