Integrative Information Management for Systems Biology
Integrative Information Management for Systems Biology
复制标题
系统生物学综合信息管理
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
N. Paton
中科院分区：
文献类型：
--
作者：
Neil Swainston;Daniel Jameson;P. Li;Irena Spasic;P. Mendes;N. Paton
系统生物学开发了生物系统的数学模型，旨在解释或更好地预测系统的行为方式。在自下而上的系统生物学中，进行系统的定量实验以获得参数化模型所需的数据，然后可以进行分析和模拟。本文介绍了一种集成的信息管理方法，支持自下而上的系统生物学，以自动化，或至少最大限度地减少手动工作期间，从定性模型和实验数据的定量模型的创建。自动化过程使模型构建更加系统化，支持管道中所有阶段的良好实践，并允许将高通量实验结果及时集成到模型中。
Systems biology develops mathematical models of biological systems that seek to explain, or better still predict, how the system behaves. In bottom-up systems biology, systematic quantitative experimentation is carried out to obtain the data required to parameterize models, which can then be analyzed and simulated. This paper describes an approach to integrated information management that supports bottom-up systems biology, with a view to automating, or at least minimizing the manual effort required during, creation of quantitative models from qualitative models and experimental data. Automating the process makes model construction more systematic, supports good practice at all stages in the pipeline, and allows timely integration of high throughput experimental results into models.