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TECHNIQUES FOR PREDICTING PHENOTYPE FROM GENOTYPE BASED ON A WHOLE CELL COMPUTATIONAL MODEL
TECHNIQUES FOR PREDICTING PHENOTYPE FROM GENOTYPE BASED ON A WHOLE CELL COMPUTATIONAL MODEL
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机译:基于全细胞计算模型的基因型表型预测技术
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摘要
Techniques for simulations using a whole-cell model include retrieving cell state data that indicates chromosome data that represents over 40 %, and preferably 100%, of genes in a single cell of an organism, and which also indicates populations of gene products in multiple functional compartments. The compartments include, at least, an external conditions compartment, a membrane compartment, a cytosol compartment, and a DNA interactions compartment. Multiple sub-models are executed that each simulate, for a same time step, a different cell process selected from, at least, transcription, translation, ribosome assembly, protein translocation, and metabolism. Values for the cell state data are updated based on results from executing the sub-models; and, the steps of executing the sub-models and updating the values for the cell state data are repeated for multiple time steps. Values of the cell state data after the multiple time steps are stored on a computer-readable medium.
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