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» Analysis techniques for microarray time-series data
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BMCBI
2010
96views more  BMCBI 2010»
13 years 8 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
CMSB
2006
Springer
14 years 11 days ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
BMCBI
2010
151views more  BMCBI 2010»
13 years 8 months ago
BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets
Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design ...
Mark J. Alston, John Seers, Jay C. D. Hinton, Sach...
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
14 years 1 months ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
AAAI
2007
13 years 11 months ago
Biomind ArrayGenius and GeneGenius: Web Services Offering Microarray and SNP Data Analysis via Novel Machine Learning Methods
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
Ben Goertzel, Cassio Pennachin, Lúcio de So...