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BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
KDD
2007
ACM
156views Data Mining» more  KDD 2007»
14 years 7 months ago
Estimating rates of rare events at multiple resolutions
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
13 years 11 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Inference of haplotypic phase and missing genotypes in polyploid organisms and variable copy number genomic regions
Background: The power of haplotype-based methods for association studies, identification of regions under selection, and ancestral inference, is well-established for diploid organ...
Shu-Yi Su, Jonathan White, David J. Balding, Lachl...
CORR
2010
Springer
168views Education» more  CORR 2010»
13 years 5 months ago
Gaussian Process Structural Equation Models with Latent Variables
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
Ricardo Silva