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引用本文的文献

1
Validation of a computational platform for the analysis of the physiologic mechanisms of a human experimental model of hemorrhage.验证一种用于分析人体出血实验模型生理机制的计算平台。
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系统生理学技术和检验复杂假设方法的进展。

Strides in the technology of systems physiology and the art of testing complex hypotheses.

作者信息

Bassingthwaighte J B

出版信息

Fed Proc. 1987 Jun;46(8):2473-6.

PMID:3297794
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4132062/
Abstract

Scientific understanding in physics or physiology is based on models or theories devised to describe what is known, within the limits imposed by observation error. Carefully integrated models can be used for prediction, and the inferences assessed via further experiments designed to test the adequacy of the theory summarizing the state of knowledge. This is the systems approach, the basis of theoretical physiology; the models, like those of theoretical physics, should be firmly based on fundamental reproducible observations of a physical or chemical nature, held together with the principles of mathematics, logic, and the conservation of mass and energy. Modern computing power is such that comprehensive models can now be constructed and tested. For this approach data sets should include as many simultaneously obtained items of information of differing sorts as possible to reduce the degrees of freedom in fitting models to data. By taking advantage of large memories and rapid computation, modular construction techniques permit the formulation of multimodels covering more than a single hierarchical level, and thereby allow the investigator to understand the effects of controllers at the molecular level on overall cell or organism behavior. How does this influence the research and teaching practices of physiology? Because the computer also allows a new type of collaboration involving the networking of ideas, data bases, analytical techniques, and experiment designing, investigators in geographically distributed individual laboratories can plan, work, and analyze in concert. The prediction from this socioscientific model is therefore that networked computer-based modeling will serve to coalesce the ideas and observations of enlarging groups of investigators.

摘要

物理学或生理学中的科学理解基于为描述已知内容而设计的模型或理论,这些模型或理论受观测误差的限制。精心整合的模型可用于预测,并通过进一步设计的实验来评估推断,这些实验旨在检验总结知识状态的理论的充分性。这就是系统方法,即理论生理学的基础;这些模型,如同理论物理学的模型一样,应牢固地基于物理或化学性质的基本可重复观测,并结合数学、逻辑以及质量和能量守恒原理。现代计算能力使得现在能够构建和测试综合模型。对于这种方法,数据集应尽可能包含尽可能多的同时获取的不同种类信息项,以减少模型与数据拟合中的自由度。借助大容量内存和快速计算,模块化构建技术允许制定涵盖多个层次水平的多模型,从而使研究者能够理解分子水平上的控制器对细胞或生物体整体行为的影响。这如何影响生理学的研究和教学实践呢?因为计算机还允许一种新型的合作,涉及思想、数据库、分析技术和实验设计的网络化,分布在不同地理位置的各个实验室的研究者能够协同规划、开展工作和进行分析。因此,从这种社会科学模型得出的预测是,基于网络计算机的建模将有助于整合越来越多研究者的思想和观测结果。