发帖
雷达卡
摘要翻译：
计算方法重塑了现代生物学的面貌。虽然生物医学界越来越依赖于计算工具，但确保开放数据、开放软件和可重复性的机制由学术机构、资助者和出版商执行。出版物可能会提供一些学术软件，这些软件的基本材料是不可用的，也可能是不可用的，如源代码和文档。缺乏此类信息的出版物损害了同行审查在评估技术实力和科学贡献方面的作用。学术软件包的不完整辅助信息可能会偏见或限制使用该工具产生的任何后续工作。我们在四个不同的领域提供了八个建议，以提高计算生物学的可重复性、透明性和严谨性--正是在生命科学课程中应该强调的主要价值。我们为提高软件可用性、可用性和档案稳定性提出的建议旨在促进生物医学和生命科学研究中可持续的数据科学生态系统。
---
英文标题：
《Recommendations to enhance rigor and reproducibility in biomedical
research》
---
作者：
Jaqueline J. Brito, Jun Li, Jason H. Moore, Casey S. Greene, Nicole A.
Nogoy, Lana X. Garmire, Serghei Mangul
---
最新提交年份：
2020
---
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
--
---
英文摘要：
Computational methods have reshaped the landscape of modern biology. While the biomedical community is increasingly dependent on computational tools, the mechanisms ensuring open data, open software, and reproducibility are variably enforced by academic institutions, funders, and publishers. Publications may present academic software for which essential materials are or become unavailable, such as source code and documentation. Publications that lack such information compromise the role of peer review in evaluating technical strength and scientific contribution. Incomplete ancillary information for an academic software package may bias or limit any subsequent work produced with the tool. We provide eight recommendations across four different domains to improve reproducibility, transparency, and rigor in computational biology - precisely on the main values which should be emphasized in life science curricula. Our recommendations for improving software availability, usability, and archival stability aim to foster a sustainable data science ecosystem in biomedicine and life science research.
---
PDF链接：
https://arxiv.org/pdf/2001.05127
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
京公网安备 11010802022788号
