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» Clustering gene expression patterns
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BIBE
2004
IEEE
160views Bioinformatics» more  BIBE 2004»
15 years 8 months ago
A Time Series Analysis of Microarray Data
As the capture and analysis of single-time-point microarray expression data becomes routine, investigators are turning to time-series expression data to investigate complex gene r...
Selnur Erdal, Ozgur Ozturk, David L. Armbruster, H...
BMCBI
2006
186views more  BMCBI 2006»
15 years 4 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
SAC
2002
ACM
15 years 3 months ago
Short inversions and conserved gene clusters
Two independent sets of recent observations on newly sequenced microbial genomes pertain to the prevalence of short inversion as a gene order rearrangement process and to the lack...
David Sankoff
BMCBI
2010
214views more  BMCBI 2010»
15 years 4 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
BMCBI
2010
161views more  BMCBI 2010»
15 years 4 months ago
GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms
Background: An important objective of DNA microarray-based gene expression experimentation is determining interrelationships that exist between differentially expressed genes and ...
Saurin D. Jani, Gary L. Argraves, Jeremy L. Barth,...