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Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery

机译:按规则进行系统生物学:用于路径建模和发现的混合智能系统

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摘要

BackgroundExpert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication.
机译:背景期刊文章中的专家知识是重建生物学途径和创建新假设的重要数据来源。医学研究的一项重要需求是将这些数据与高通量资源集成在一起,以构建涵盖多个规模的有用模型。传统上,研究人员使用途径的心理模型来整合信息并开发新的假设。不幸的是,信息量通常不堪重负,而这些信息不足以预测复杂途径的动态响应。允许探索半定量动力学的分层计算模型对于理论家,实验家和临床医生是有用的系统生物学工具,并且可以提供交叉交流的手段。

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