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» Bayesian Networks Learning for Gene Expression Datasets
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BMCBI
2008
160views more  BMCBI 2008»
14 years 12 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
NAR
2002
141views more  NAR 2002»
14 years 11 months ago
Co-expression pattern from DNA microarray experiments as a tool for operon prediction
The prediction of operons, the smallest unit of transcription in prokaryotes, is the first step towards reconstruction of a regulatory network at the whole genome level. Sequence ...
Chiara Sabatti, Lars Rohlin, Min-Kyu Oh, James C. ...
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BMCBI
2010
164views more  BMCBI 2010»
14 years 12 months ago
Gene regulatory networks modelling using a dynamic evolutionary hybrid
Background: Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With ...
Ioannis A. Maraziotis, Andrei Dragomir, Dimitris T...
BMCBI
2010
172views more  BMCBI 2010»
14 years 12 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
CDC
2009
IEEE
179views Control Systems» more  CDC 2009»
15 years 4 months ago
Bayesian network approach to understand regulation of biological processes in cyanobacteria
— Bayesian networks have extensively been used in numerous fields including artificial intelligence, decision theory and control. Its ability to utilize noisy and missing data ...
Thanura R. Elvitigala, Abhay K. Singh, Himadri B. ...