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TECHNIQUES FOR PREDICTING PHENOTYPE FROM GENOTYPE BASED ON A WHOLE CELL COMPUTATIONAL MODEL

机译:基于全细胞计算模型的基因型表型预测技术

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.
机译:使用全细胞模型进行模拟的技术包括检索细胞状态数据,该数据表示代表生物体单个细胞中40%以上(最好是100%)的基因的染色体数据,并且还表明具有多种功能的基因产物群体隔间。所述隔室至少包括外部条件隔室,膜隔室,细胞溶胶隔室和DNA相互作用隔室。执行多个子模型,每个子模型在相同的时间步骤中模拟至少选自转录,翻译,核糖体装配,蛋白质易位和代谢的不同细胞过程。单元状态数据的值基于执行子模型的结果进行更新。并且,对于多个时间步骤,重复执行子模型和更新单元状态数据的值的步骤。在多个时间步骤之后的单元状态数据的值被存储在计算机可读介质上。

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