论文标题
保持潜在，而不是回顾：在现代生物学研究中提高可重复性的哲学
Be Prospective, Not Retrospective: A Philosophy for Advancing Reproducibility in Modern Biological Research
论文作者
论文摘要
现代科学研究中计算的无处不在为可重复性带来了新的挑战。尽管大多数期刊现在都需要代码和数据可用，但组织，注释和验证的标准仍然很宽松，这使得数据和代码通常很难解密或实际使用。我相信这是由于文档，整理和验证代码和数据仅在回顾中进行。在本文中，我反思了与这些挑战有关的经验，并提出了在现代生物学研究中优先考虑可重复性的哲学，在现代生物学研究中，平衡计算分析和湿LAB实验是司空见惯的。在科学工作流中使用的现代工具（例如GitHub存储库）很好地借鉴了这种理念，在该理念中，重现性始于项目启动而不是完成。为此，我介绍并提供了一个编程语言不可知的模板架构，可以立即复制并定制下一篇论文，无论您的实验室工作是湿，干还是介于两者之间的地方。
The ubiquity of computation in modern scientific research inflicts new challenges for reproducibility. While most journals now require code and data be made available, the standards for organization, annotation, and validation remain lax, making the data and code often difficult to decipher or practically use. I believe that this is due to the documentation, collation, and validation of code and data only being done in retrospect. In this essay, I reflect on my experience contending with these challenges and present a philosophy for prioritizing reproducibility in modern biological research where balancing computational analysis and wet-lab experiments is commonplace. Modern tools used in scientific workflows (such as GitHub repositories) lend themselves well to this philosophy where reproducibility begins at project inception, not completion. To that end, I present and provide a programming-language agnostic template architecture that can be immediately copied and made bespoke to your next paper, whether your lab work is wet, dry, or somewhere in between.
