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BIOCOMP
2006
13 years 6 months ago
Finding Molecular Signature of Prostate Cancer: An Algorithmic Approach
123 African American men in America are 65% more likely to develop prostate cancer and are two to three times more likely to die of the disease than Caucasian men [1]. While resear...
Patrick Bobbie, Renee Reams, Sandra Suther, C. Per...
JAMIA
2011
94views more  JAMIA 2011»
12 years 7 months ago
Protein-network modeling of prostate cancer gene signatures reveals essential pathways in disease recurrence
Objective Uncovering the dominant molecular deregulation among the multitude of pathways implicated in aggressive prostate cancer is essential to intelligently developing targeted...
James L. Chen, Jianrong Li, Walter M. Stadler, Yve...
BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
13 years 10 months 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
CEC
2007
IEEE
13 years 8 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...