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BMCBI
2008
160views more  BMCBI 2008»
13 years 7 months ago
A method for analyzing censored survival phenotype with gene expression data
Background: Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles a...
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Ch...
BMCBI
2008
169views more  BMCBI 2008»
13 years 7 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
BMCBI
2006
82views more  BMCBI 2006»
13 years 7 months ago
Profiling alternatively spliced mRNA isoforms for prostate cancer classification
Background: Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomar...
Chaolin Zhang, Hai-Ri Li, Jian-Bing Fan, Jessica W...
BMCBI
2010
133views more  BMCBI 2010»
13 years 7 months ago
Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines
Background: Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic react...
Limin Li, Xiaobo Zhou, Wai-Ki Ching, Ping Wang
BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta