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BMCBI
2010
164views more  BMCBI 2010»
14 years 7 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BMCBI
2011
14 years 5 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
15 years 10 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
ISPASS
2010
IEEE
15 years 4 months ago
Visualizing complex dynamics in many-core accelerator architectures
—While many-core accelerator architectures, such as today’s Graphics Processing Units (GPUs), offer orders of magnitude more raw computing power than contemporary CPUs, their m...
Aaron Ariel, Wilson W. L. Fung, Andrew E. Turner, ...
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
15 years 2 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel