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BMCBI
2008
129views more  BMCBI 2008»
13 years 11 months ago
EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management
Background: Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large d...
Geraint Barton, J. C. Abbott, Norie Chiba, D. W. H...
BMCBI
2007
174views more  BMCBI 2007»
13 years 11 months ago
Inferring activity changes of transcription factors by binding association with sorted expression profiles
Background: The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data,...
Chao Cheng, Xiting Yan, Fengzhu Sun, Lei M. Li
BMCBI
2008
128views more  BMCBI 2008»
13 years 11 months ago
Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sa
Background: In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a sign...
Cornelia Frömke, Ludwig A. Hothorn, Siegfried...
BMCBI
2010
112views more  BMCBI 2010»
13 years 11 months ago
Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships
Background: The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. Wh...
Junhee Seok, Amit Kaushal, Ronald W. Davis, Wenzho...
BIOSYSTEMS
2007
115views more  BIOSYSTEMS 2007»
13 years 11 months ago
Evolving fuzzy rules to model gene expression
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Ricardo Linden, Amit Bhaya
BMCBI
2010
100views more  BMCBI 2010»
13 years 11 months ago
A robust method for estimating gene expression states using Affymetrix microarray probe level data
Background: Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-speci...
Megu Ohtaki, Keiko Otani, Keiko Hiyama, Naomi Kame...
BMCBI
2010
172views more  BMCBI 2010»
13 years 11 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
BMCBI
2010
129views more  BMCBI 2010»
13 years 11 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
BMCBI
2010
214views more  BMCBI 2010»
13 years 11 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BIOINFORMATICS
2007
50views more  BIOINFORMATICS 2007»
13 years 11 months ago
Exploiting sample variability to enhance multivariate analysis of microarray data
Page 1 of 2Exploiting sample variability to enhance multivariate analysis of microarray data -- Möller-Le... http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/20/2...
Carla S. Möller-Levet, Catharine M. West, Cri...