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A whole-cell computational model predicts phenotype from genotype

聚焦生物添加于 2012-12-26 19:56 | 1687 次阅读 | 0 个评论

作者
Karr JR, Sanghvi JC, Macklin DN, Gutschow MV, Jacobs JM, Bolival BJ, Assad-Garcia N, Glass JI, Covert MW
摘要
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. 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.
详细资料
- 关键词: Bacterial Proteins/metabolism; Cell Cycle; *Computer Simulation; DNA-Binding Proteins/metabolism; *Models, Biological; Molecular Sequence Annotation; Mycoplasma genitalium/*cytology/*genetics; Phenotype
- 文献种类: Journal Article
- 期刊名称: Cell
- 期刊缩写: Cell
- 期卷页: 2012年第150卷第2期 389-401页
- 地址: Graduate Program in Biophysics, Stanford University, Stanford, CA 94305, USA
- ISBN: 0092-8674
学科领域生物医药 » 生物学
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附件
A whole-cell computational model predicts phenotype from genotype