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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2010
152views more  BMCBI 2010»
13 years 9 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...
WABI
2005
Springer
14 years 2 months ago
Time-Window Analysis of Developmental Gene Expression Data with Multiple Genetic Backgrounds
d Abstract] Tamir Tuller , Efrat Oron , Erez Makavy , Daniel A. Chamovitz † , and Benny Chor ‡ Tel-Aviv University, Tel-Aviv 69978, Israel. Abstract. We study gene expression d...
Tamir Tuller, Efrat Oron, Erez Makavy, Daniel A. C...
BMCBI
2008
122views more  BMCBI 2008»
13 years 9 months ago
Determining gene expression on a single pair of microarrays
Background: In microarray experiments the numbers of replicates are often limited due to factors such as cost, availability of sample or poor hybridization. There are currently fe...
Robert W. Reid, Anthony A. Fodor
BMCBI
2005
97views more  BMCBI 2005»
13 years 8 months ago
Modelling the correlation between the activities of adjacent genes in drosophila
Background: Correlation between the expression levels of genes which are located close to each other on the genome has been found in various organisms, including yeast, drosophila...
Helene H. Thygesen, Aeilko H. Zwinderman
BMCBI
2007
133views more  BMCBI 2007»
13 years 8 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...