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» Smoothing Gene Expression Using Biological Networks
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ISMB
1997
13 years 10 months ago
Functional Prediction of B. subtilis Genes from Their Regulatory Sequences
In bacterial cells, gene expression is regulated by multiple sigma factors, each of which has its promoter specificity, according to their conditions. Thus, if we can discriminate...
Tetsushi Yada, Yasushi Totoki, Takahiro Ishii, Ken...
ICCS
2003
Springer
14 years 2 months ago
Modelling Developmental Regulatory Networks
Abstract. This paper introduces a model for simulating regulatory networks that is capable of reproducing spatial and temporal expression patterns in developmental processes. The m...
Tommy Krul, Jaap A. Kaandorp, Joke G. Blom
ICANN
2009
Springer
13 years 6 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
BMCBI
2010
144views more  BMCBI 2010»
13 years 9 months ago
Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model
Background: Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is gen...
Xin He, Moushumi Sen Sarma, Xu Ling, Brant W. Chee...
BMCBI
2005
98views more  BMCBI 2005»
13 years 8 months ago
The effects of normalization on the correlation structure of microarray data
Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...