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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2007
78views more  BMCBI 2007»
14 years 10 months ago
Improved human disease candidate gene prioritization using mouse phenotype
Background: The majority of common diseases are multi-factorial and modified by genetically and mechanistically complex polygenic interactions and environmental factors. High-thro...
Jing Chen, Huan Xu, Bruce J. Aronow, Anil G. Jegga
BMCBI
2007
131views more  BMCBI 2007»
14 years 10 months ago
FUNC: a package for detecting significant associations between gene sets and ontological annotations
Background: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Informatio...
Kay Prüfer, Bjoern Muetzel, Hong Hai Do, Gunt...
BMCBI
2010
125views more  BMCBI 2010»
14 years 10 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
BMCBI
2010
152views more  BMCBI 2010»
14 years 10 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
BMCBI
2010
178views more  BMCBI 2010»
14 years 10 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...