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» Classification of microarray data using gene networks
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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 9 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
BMCBI
2005
101views more  BMCBI 2005»
15 years 3 months ago
MASQOT: a method for cDNA microarray spot quality control
Background: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying ...
Max Bylesjö, Daniel Eriksson, Andreas Sjö...
BMCBI
2011
14 years 7 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
ITA
2006
167views Communications» more  ITA 2006»
15 years 3 months ago
Characterization of lung tumor subtypes through gene expression cluster validity assessment
The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at b...
Giorgio Valentini, Francesca Ruffino
BMCBI
2008
132views more  BMCBI 2008»
15 years 3 months ago
Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of
Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
Raffaele Giancarlo, Davide Scaturro, Filippo Utro