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» Evaluation of clustering algorithms for gene expression data
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PAKDD
2009
ACM
225views Data Mining» more  PAKDD 2009»
16 years 3 months ago
Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...
CLUSTER
2008
IEEE
16 years 1 months ago
Enabling lock-free concurrent fine-grain access to massive distributed data: Application to supernovae detection
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
Bogdan Nicolae, Gabriel Antoniu, Luc Bougé
BMCBI
2010
118views more  BMCBI 2010»
15 years 6 months ago
Detecting lateral gene transfers by statistical reconciliation of phylogenetic forests
Background: To understand the evolutionary role of Lateral Gene Transfer (LGT), accurate methods are needed to identify transferred genes and infer their timing of acquisition. Ph...
Sophie S. Abby, Eric Tannier, Manolo Gouy, Vincent...
CEC
2007
IEEE
16 years 27 days ago
A co-evolutionary framework for regulatory motif discovery
Abstract— In previous work, we have shown how an evolutionary algorithm with a clustered population can be used to concurrently discover multiple regulatory motifs present within...
Michael A. Lones, Andy M. Tyrrell
ICMLA
2008
15 years 8 months ago
Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes
When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
Cecilia Sönströd, Ulf Johansson, Ulf Nor...