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ISMB
2000
13 years 10 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
ICCAD
2005
IEEE
81views Hardware» more  ICCAD 2005»
14 years 5 months ago
Kauffman networks: analysis and applications
Abstract— A Kauffman network is an abstract model of gene regulatory networks. Each gene is represented by a vertex. An edge from one vertex to another implies that the former ge...
Elena Dubrova, Maxim Teslenko, Andrés Marti...
BMCBI
2007
120views more  BMCBI 2007»
13 years 9 months ago
Recognition of interferon-inducible sites, promoters, and enhancers
Background: Computational analysis of gene regulatory regions is important for prediction of functions of many uncharacterized genes. With this in mind, search of the target genes...
Elena A. Ananko, Yury V. Kondrakhin, Tatyana I. Me...
ICMLA
2010
13 years 6 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
BMCBI
2007
99views more  BMCBI 2007»
13 years 9 months ago
Towards validating the hypothesis of phylogenetic profiling
Background: As the number of fully sequenced genome increases, the need is greater for bioinformatics to predict or annotate genes of a newly sequenced genome. Ever since Eisenber...
Raja Loganantharaj, Mazen Atwi