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» On the Expressive Power of QLTL
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219
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APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 7 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
BMCBI
2008
166views more  BMCBI 2008»
15 years 6 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
AIR
2006
124views more  AIR 2006»
15 years 6 months ago
Expressiveness of temporal query languages: on the modelling of intervals, interval relationships and states
Abstract Storing and retrieving time-related information are important, or even critical, tasks on many areas of Computer Science (CS) and in particular for Artificial Intelligence...
Rodolfo Sabás Gómez, Juan Carlos Aug...
188
Voted
BMCBI
2004
205views more  BMCBI 2004»
15 years 5 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
CEC
2003
IEEE
15 years 9 months ago
Dynamics of gene expression in an artificial genome
Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulator...
Kai Willadsen, Janet Wiles