Ant Colony Optimization for Inferring Key Gene Interactions
This work addresses the need for identifying biomarkers in disease research, but it is incremental as it applies an existing optimization method to a known task.
The paper tackled the problem of inferring key gene interactions from gene expression data using ant colony optimization, and the result was that the algorithm successfully identified some key interactions on two benchmark datasets.
Inferring gene interaction network from gene expression data is an important task in systems biology research. The gene interaction network, especially key interactions, plays an important role in identifying biomarkers for disease that further helps in drug design. Ant colony optimization is an optimization algorithm based on natural evolution and has been used in many optimization problems. In this paper, we applied ant colony optimization algorithm for inferring the key gene interactions from gene expression data. The algorithm has been tested on two different kinds of benchmark datasets and observed that it successfully identify some key gene interactions.