Sciweavers

980 search results - page 82 / 196
» Smoothing Gene Expression Using Biological Networks
Sort
View
GECCO
1999
Springer
130views Optimization» more  GECCO 1999»
14 years 1 months ago
Heterochrony and Adaptation in Developing Neural Networks
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The model’s results are analyzed using the fra...
Angelo Cangelosi
CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
14 years 2 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
BMCBI
2007
169views more  BMCBI 2007»
13 years 9 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 10 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
DILS
2009
Springer
14 years 3 months ago
Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes
Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to spe...
Katherine James, Anil Wipat, Jennifer Hallinan