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BMCBI
2010
214views more  BMCBI 2010»
13 years 7 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
98views more  BMCBI 2010»
13 years 7 months ago
A semi-nonparametric mixture model for selecting functionally consistent proteins
Background: High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experim...
Lianbo Yu, R. W. Doerge
AI
2006
Springer
13 years 11 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
BIODATAMINING
2008
135views more  BIODATAMINING 2008»
13 years 7 months ago
Fast Gene Ontology based clustering for microarray experiments
Background: Analysis of a microarray experiment often results in a list of hundreds of diseaseassociated genes. In order to suggest common biological processes and functions for t...
Kristian Ovaska, Marko Laakso, Sampsa Hautaniemi
BMCBI
2007
105views more  BMCBI 2007»
13 years 7 months ago
Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor sti
Background: High-throughput experiments, such as with DNA microarrays, typically result in hundreds of genes potentially relevant to the process under study, rendering the interpr...
Rob Jelier, Guido Jenster, Lambert C. J. Dorssers,...