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» Additive risk survival model with microarray data
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SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
14 years 11 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
BMCBI
2006
126views more  BMCBI 2006»
14 years 9 months ago
OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments
Background: Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no...
Morgan N. Price, Adam P. Arkin, Eric J. Alm
WEBI
2010
Springer
14 years 7 months ago
An Approach to Model and Predict the Popularity of Online Contents with Explanatory Factors
In this paper, we propose a methodology to predict the popularity of online contents. More precisely, rather than trying to infer the popularity of a content itself, we infer the l...
Jong Gun Lee, Sue Moon, Kavé Salamatian
EMISA
2010
Springer
14 years 4 months ago
Investigating the Process of Process Modeling with Cheetah Experimental Platform
Abstract. When assessing the usability of BPM technologies enterprises have to rely on vendor promises or qualitative data rather than on empirical or experimental research. To add...
Jakob Pinggera, Stefan Zugal, Barbara Weber
EMO
2005
Springer
108views Optimization» more  EMO 2005»
15 years 3 months ago
Multi-objective Model Optimization for Inferring Gene Regulatory Networks
With the invention of microarray technology, researchers are able to measure the expression levels of ten thousands of genes in parallel at various time points of a biological proc...
Christian Spieth, Felix Streichert, Nora Speer, An...