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Using Bayesian networks to analyze expression data

by Nir Friedman, Michal Linial, Iftach Nachman - Journal of Computational Biology , 2000
"... DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a “snapshot ” of transcription levels within the cell. A major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key biologica ..."
Abstract - Cited by 1088 (17 self) - Add to MetaCart
by showing how Bayesian networks can describe interactions between genes. We then describe a method for recovering gene interactions from microarray data using tools for learning Bayesian networks. Finally, we demonstrate this method on the S. cerevisiae cell-cycle measurements of Spellman et al. (1998). Key

KEGG: Kyoto Encyclopedia of Genes and Genomes

by Hiroyuki Ogata, Susumu Goto, Kazushige Sato, Wataru Fujibuchi, Hidemasa Bono - Nucl. Acids Res , 1999
"... Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known me ..."
Abstract - Cited by 408 (0 self) - Add to MetaCart
efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available

Reverse engineering of regulatory networks in human B cells.

by Katia Basso , Adam A Margolin , Gustavo Stolovitzky , Ulf Klein , Riccardo Dalla-Favera , Andrea Califano - Nat. Genet. , 2005
"... Cellular phenotypes are determined by the differential activity of networks linking coregulated genes. Available methods for the reverse engineering of such networks from genome-wide expression profiles have been successful only in the analysis of lower eukaryotes with simple genomes. Using a new m ..."
Abstract - Cited by 178 (2 self) - Add to MetaCart
method called ARACNe (algorithm for the reconstruction of accurate cellular networks), we report the reconstruction of regulatory networks from expression profiles of human B cells. The results are suggestive a hierarchical, scale-free network, where a few highly interconnected genes (hubs) account

Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks

by Dirk Husmeier - Bioinformatics , 2003
"... Motivation: Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data. This inference problem is particularly hard in that interactions between hundreds of genes have to be learned from very small data sets, typically containing only a few doze ..."
Abstract - Cited by 174 (5 self) - Add to MetaCart
Motivation: Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data. This inference problem is particularly hard in that interactions between hundreds of genes have to be learned from very small data sets, typically containing only a few

A visual data mining tool that facilitates reconstruction of transcription regulatory networks

by Daniel C. Jupiter, Vincent Vanburen - PLoS ONE , 2008
"... Background: Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clu ..."
Abstract - Cited by 14 (0 self) - Add to MetaCart
addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed metaanalysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2

Qualitative Simulation of Genetic Regulatory Networks Using Piecewise-Linear Models

by Hidde De Jong, Jean-Luc Gouze, Celine Hernandez, Michel Page, Tewfik Sari, Johannes Geiselmann , 2001
"... In order to cope with the large amounts of data that have become available in genomics, mathematical tools for the analysis of networks of interactions between genes, proteins, and other molecules are indispensable. We present a method for the qualitative simulation of genetic regulatory networks ..."
Abstract - Cited by 190 (30 self) - Add to MetaCart
In order to cope with the large amounts of data that have become available in genomics, mathematical tools for the analysis of networks of interactions between genes, proteins, and other molecules are indispensable. We present a method for the qualitative simulation of genetic regulatory

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data

by C. C. Wu, H. C. Huang, H. F. Juan, S. T. Chen - BIOINFORMATICS , 2004
"... Recently a variety of high-troughput experimental techniques, such as DNA microarray, are opening system-level perspectives of living organisms on the molecular level. Inferring genetic network architecture from time series data generated from these technologies is an important computational methods ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
methods to help us to understand the system behavior of living organisms. We developed an interactive software, GeneNetwork, which supports four representative reverse engineering models and three data interpolation approaches. It enables users readily reconstruct genetic network based on microarray data

Reconstructing Directed Signed Gene Regulatory Network from Microarray Data

by Peng Qiu, Sylvia K. Plevritis
"... Abstract—Great efforts have been made to develop both algorithms that reconstruct gene regulatory networks and sys-tems that simulate gene networks and expression data, for the purpose of benchmarking network reconstruction algorithms. An interesting observation is that although many simulation syst ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
Abstract—Great efforts have been made to develop both algorithms that reconstruct gene regulatory networks and sys-tems that simulate gene networks and expression data, for the purpose of benchmarking network reconstruction algorithms. An interesting observation is that although many simulation

Article Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

by Alina Sîrbu, Martin Crane, Heather J. Ruskin
"... microarrays ..."
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microarrays

Modelling and analysis of gene regulatory networks,

by Guy Karlebach , Ron Shamir - Nat Rev Mol Cell Biol , 2008
"... The genome encodes thousands of genes whose pro ducts enable cell survival and numerous cellular func tions. The amounts and the temporal pattern in which these products appear in the cell are crucial to the pro cesses of life. Gene regulatory networks govern the levels of these gene products. A ge ..."
Abstract - Cited by 118 (2 self) - Add to MetaCart
and can reveal the mechanisms that underlie them. Consequently, biologists must come to grips with extremely complex networks and must analyse and integrate great quantities of experimental data. Essential to this challenge are computational tools, which can answer various questions: what is the full
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