Naoki Hosoyama (firstname.lastname@example.org)
Noman Nasimul (email@example.com)
Hitoshi Iba (firstname.lastname@example.org)
Department of Electronics Engineering, University of Tokyo, Japan
Department of Frontier Informatics, University of Tokyo, Japan
In recent years, base sequences have been increasingly unscrambled through attempts represented by the human genome project. Accordingly, the estimation of the genetic network has been accelerated. However, no definitive method has become available for drawing a large effective graph. This paper proposes a method which allows for coping with an increase in the number of nodes by laying out genes on planes of several layers and then overlapping these planes. This layout involves an optimization problem which requires maximizing the fitness function. To demonstrate the effectiveness of our approach, we show some graphs using actual data on 82 genes and 552 genes. We also describe how to lay out nodes by means of stochastic searches, e.g., stochastic hill-climbing and incremental methods. The experimental results show the superiority and usefulness of two search methods in comparison with the simple random search.