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BMCBI
2004
206views more  BMCBI 2004»
13 years 7 months ago
Combining gene expression data from different generations of oligonucleotide arrays
Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public re...
Kyu Baek Hwang, Sek Won Kong, Steven A. Greenberg,...
BMCBI
2007
207views more  BMCBI 2007»
13 years 7 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
JAIR
2008
157views more  JAIR 2008»
13 years 7 months ago
Qualitative System Identification from Imperfect Data
Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to ...
George Macleod Coghill, Ashwin Srinivasan, Ross D....
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
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
14 years 15 days ago
Identifying Gene Signatures from Cancer Progression Data Using Ordinal Analysis
—A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and it may provide much needed information for effective d...
Yoon Soo Pyon, Jing Li