Abstract:
:By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized.
journal_name
Nucleic Acids Resjournal_title
Nucleic acids researchauthors
Fang G,Zhang S,Dong Ydoi
10.1093/nar/gkx859subject
Has Abstractpub_date
2017-12-15 00:00:00pages
e182issue
22eissn
0305-1048issn
1362-4962pii
4259025journal_volume
45pub_type
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