Rough set methods are often employed for reducting decision rules. The specific techniques involving rough sets can be carried out in a computational manner. However, they are quite demanding when it comes computing overhead. In particular, it becomes problematic to compute all minimal length decision rules while dealing with a large number of decision rules. This results in an NP-hard problem. To address this computational challenge, in this study, we propose a method of DNA rough-set computing composed of computational DNA molecular techniques used for decision rule reducts. This method can be effectively employed to alleviate the computational complexity of the problem.