前瞻性，而不是回顾性：现代生物学研究中促进生殖的哲学
Be Prospective, Not Retrospective: A Philosophy for Advancing Reproducibility in Modern Biological Research
摘要：
计算在现代科学研究中无处不在，这给可重复性带来了新的挑战。虽然现在大多数期刊都要求提供代码和数据，但组织，注释和验证的标准仍然很宽松，使得数据和代码通常难以破译或实际使用。我相信这是由于文档、校对和代码和数据的验证只在回顾中完成。在这篇文章中，我反思了我与这些挑战竞争的经验，并提出了一种在现代生物学研究中优先考虑再现性的哲学，在现代生物学研究中，平衡计算分析和湿实验室实验是司空见惯的。科学工作流中使用的现代工具（如GitHub存储库）很好地适应了这种理念，即可重复性始于项目开始，而不是完成。为此，我提出并提供了一个与编程语言无关的模板架构，无论你的实验室工作是湿的、干的还是介于两者之间，都可以立即复制并定制到你的下一篇论文中。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
