By successively assembling genetic parts according to grammatical models, complex genetic constructs can be built. However, every category of genetic parts includes many parts. With the increasing quantity of genetic… Click to show full abstract
By successively assembling genetic parts according to grammatical models, complex genetic constructs can be built. However, every category of genetic parts includes many parts. With the increasing quantity of genetic parts, the process of assembling a few sets of genetic parts can be costly, time consuming, and error prone. At the final assembly step, it is difficult to decide which part should be selected. Based on a statistical language model, a dynamic programming algorithm was designed to solve this problem. The algorithm optimizes the results of genetic designs and finds an optimal solution. In this way, redundant operations can be reduced, and the cost for assembling can be minimized.
               
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