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» Additive risk survival model with microarray data
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BMCBI
2011
12 years 11 months ago
Sequential Interim Analyses of Survival Data in DNA Microarray Experiments
Background: Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Freq...
Andreas Leha, Tim Beißbarth, Klaus Jung
BMCBI
2010
123views more  BMCBI 2010»
13 years 5 months ago
Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
BMCBI
2010
150views more  BMCBI 2010»
13 years 2 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
13 years 11 months ago
Sequential Classification for Microarray and Clinical Data
Sequential classification uses in a stepwise process only part of the data (evidence) for partial classification, i.e., classifying only objects with sufficient evidence and leavi...
Günter Tusch
BMCBI
2004
158views more  BMCBI 2004»
13 years 5 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...