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.
|Journal||European Signal Processing Conference|
|Publication status||Published - Mar 27 2002|
|Event||11th European Signal Processing Conference, EUSIPCO 2002 - Toulouse, France|
Duration: Sep 3 2002 → Sep 6 2002
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering