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» Clustering Genes Using Heterogeneous Data Sources
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BMCBI
2006
138views more  BMCBI 2006»
15 years 2 months ago
Determination of strongly overlapping signaling activity from microarray data
Background: As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of...
Ghislain Bidaut, Karsten Suhre, Jean-Michel Claver...
142
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BMCBI
2008
133views more  BMCBI 2008»
15 years 2 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
CPM
2004
Springer
108views Combinatorics» more  CPM 2004»
15 years 7 months ago
Quadratic Time Algorithms for Finding Common Intervals in Two and More Sequences
A popular approach in comparative genomics is to locate groups or clusters of orthologous genes in multiple genomes and to postulate functional association between the genes contai...
Thomas Schmidt, Jens Stoye
ICDE
2009
IEEE
155views Database» more  ICDE 2009»
16 years 4 months ago
Finding Time-Lagged 3D Clusters
Existing 3D clustering algorithms on gene ? sample ? time expression data do not consider the time lags between correlated gene expression patterns. Besides, they either ignore the...
Xin Xu, Ying Lu, Kian-Lee Tan, Anthony K. H. Tung
BMCBI
2010
148views more  BMCBI 2010»
15 years 2 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney