一个如何指导生物中的代码共享的指南
Richard J Abdill1, Emma Talarico2, Laura Grieneisen2,3
1Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
PLoS biology
|September 10, 2024
概括
计算生物学对于现代生物研究至关重要. 本指南为生物学家提供了关于共享计算代码,促进开放科学原则和可重复性的实用建议.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 在生物学的开放科学.
背景情况:
- 生物学越来越依赖计算分析,湿实验室研究人员采用新的技术.
- 由于成本下降和数据集的增加,计算工具的可访问性正在增加.
- 实施计算方法的指导比报告它们的指导更容易获得,从而造成知识差距.
研究的目的:
- 为生物学家提供关于计算代码共享最佳实践的全面指南.
- 为应对新研究人员面临的挑战,在计算生物学中开放科学原则.
- 弥合计算方法实施和透明报告之间的差距.
主要方法:
- 对计算机生物学和代码共享现有文献的审查.
- 汇总了报告计算工作的常见提示和最佳实践.
- 编译资源用于培训计算生物学和开放科学.
主要成果:
- 确定生物学家在计算代码共享方面面临的关键挑战.
- 为有效共享代码制定实际建议.
- 策划相关的资源,用于进一步的学习和培训.
结论:
- 生物学家需要对共享计算代码的明确指导,以采用开放科学原则.
- 实施代码共享的最佳实践可以提高研究的透明度和可重复性.
- 这本指南是寻求改善其计算工作流程的生物学家的起点.
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