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Paper data
Pareto Analysis for Gene Filtering in Microarray Experiments

Fleury Gilles, Ecole Superieure d'Electricite
Hero Alfred, University of Michigan
Yoshida Shigeo, University of Michigan
Carter Todd, The Salk Institute
Barlow Carollee, The Salk Institute
Swaroop Anand, University of Michigan

Page numbers in the proceedings:
Volume III pp 165-168

Biomedical Processing

Paper abstract
We introduce a method for detecting strongly monotone evolutionary trends of gene expression from a temporal sequence of microarray data. In this method we perform gene filtering via multi-objective optimization to reveal genes which have the properties of: strong monotonic increase, high end-to-end slope and low slope deviation. Both a global Pareto optimization and a pair-wise local Pareto optimization are investigated. This gene filtering method is illustrated on mouse retinal genes acquired at different points over the lifetimes of a population of mice.

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