Protein expression vector optimization based on statistical language model and dynamic programming
FANG Gang
Abstract：In order to solve the problem of time consuming and error pronein selecting optimal "brick"to assemble functional protein expression vector,based on statistical language model (SLM),a dynamic program-ming algorithm of protein expression vector was carried out.By collecting the statistical parameters of BioBrick standard parts and transforming the assembling process into SLM,a dynamic programming algorithm could be performed to choose suitable parts to compose the final genetic construction.The result showed this method had high accuracy,redundant operations could be reduced and the time and cost required for conducting bio-logical experiment could be minimized.The method could be not only used to optimize a design in a synthetic biological robotic platform,but also independently used to automate the DNA assembly process in synthetic biology.It could also be iterated and then give out different optimized results for consideration.
Keywords：statistical language model(SLM)dynamic programmingprotein expression vectorBioBrick
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 88-94 )