A whole-cell computational model predicts phenotype from genotype.

A whole-cell computational model predicts phenotype from genotype.
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DOI:
10.1016/j.cell.2012.05.044
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发表时间:
2012-07-20
期刊:
影响因子:
64.5
通讯作者:
Covert MW
Covert MW
中科院分区:
生物学1区
文献类型:
--
作者:
Karr JR;Sanghvi JC;Macklin DN;Gutschow MV;Jacobs JM;Bolival B Jr;Assad-Garcia N;Glass JI;Covert MW

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Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication rates. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.
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