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摘要翻译：
最近的研究表明，在系统生物学和生理学中，大多数已发表的计算模型是不可重复或复制的。这有多种原因。最有可能的一个原因是，考虑到现代研究人员是多么忙碌，而且作者发表可重复的工作没有得到表扬，这是不可避免的。只有当政府机构、大学和其他研究机构改变政策，期刊开始坚持认为发表的作品如果不能复制，至少可以重复，这种情况才能得到纠正。在这一章中，我们描述了研究人员可以使用的指导方针，以帮助确保他们的工作是可重复的。作者可以使用一个评分系统来确定他们做得有多好。
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英文标题：
《The Practice of Ensuring Repeatable and Reproducible Computational
Models》
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作者：
Herbert M. Sauro
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最新提交年份：
2021
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Quantitative Biology 数量生物学
二级分类：Molecular Networks 分子网络
分类描述：Gene regulation, signal transduction, proteomics, metabolomics, gene and enzymatic networks
基因调控、信号转导、蛋白质组学、代谢组学、基因和酶网络
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英文摘要：
Recent studies have shown that the majority of published computational models in systems biology and physiology are not repeatable or reproducible. There are a variety of reasons for this. One of the most likely reasons is that given how busy modern researchers are and the fact that no credit is given to authors for publishing repeatable work, it is inevitable that this will be the case. The situation can only be rectified when government agencies, universities and other research institutions change policies and that journals begin to insist that published work is in fact at least repeatable if not reproducible. In this chapter guidelines are described that can be used by researchers to help make sure their work is repeatable. A scoring system is suggested that authors can use to determine how well they are doing.
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PDF链接：
https://arxiv.org/pdf/2107.05386
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