Molecular programming: evolving genetic programs in a test tube

We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for variation and selection allows for various possibilities for building novel evolvable hardware. Also, the possibility of maintaining a huge number of individuals and their massively parallel manipulation allows us to make robust decisions by the “molecular” genetic programs evolved within a single population. We evaluate the potentials of this “molecular programming” approach by solving a medical diagnosis problem on a simulated DNA computer. Here the individual genetic program represents a decision list of variable length and the whole population takes part in making probabilistic decisions. Tested on a real-life leukemia diagnosis data, the evolved molecular genetic programs showed a comparable performance to decision trees. The molecular evolutionary algorithm can be adapted to solve problems in biot...

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Byoung-Tak Zhang, Ha-Young Jang
• Keywords: GECCO 2005, Genetic Programs, Molecular, Molecular Programming