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» Bayesian Networks Learning for Gene Expression Datasets
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ICPR
2000
IEEE
15 years 4 months ago
Feature Learning for Recognition with Bayesian Networks
Many realistic visual recognition tasks are “open” in the sense that the number and nature of the categories to be learned are not initially known, and there is no closed set ...
Justus H. Piater, Roderic A. Grupen
102
Voted
BMCBI
2008
111views more  BMCBI 2008»
14 years 12 months ago
Information-based methods for predicting gene function from systematic gene knock-downs
Background: The rapid annotation of genes on a genome-wide scale is now possible for several organisms using high-throughput RNA interference assays to knock down the expression o...
Matthew T. Weirauch, Christopher K. Wong, Alexandr...
BMCBI
2010
136views more  BMCBI 2010»
14 years 12 months ago
A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles
Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful inf...
Chia-Hao Chin, Shu-Hwa Chen, Chin-Wen Ho, Ming-Tat...
EVOW
2004
Springer
15 years 5 months ago
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Carlos Cotta, Christian Sloper, Pablo Moscato
BMCBI
2006
146views more  BMCBI 2006»
14 years 11 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara