Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA,
Pac Symp Biocomput. 2020;25:739-742.
The majority of accepted papers in computational biology and biocomputing describe new software approaches to relevant biological problems. While journals and conferences often require the availability of software and source code, there are limited resources available to maximize the distribution and use of developed software within the scientific community. The accepted standard is to make source code available for new approaches in published work, the growing problem of system configuration issues, language, library version conflicts, and other implementation issues often impede the broad distribution, availability of software tools, and reproducibility of research. There are a variety of solutions to these implementation issues, but the learning curve for applying these solutions is steep. This tutorial demonstrates tools and approaches for packaging and distribution of published code, and provides methodological practices for the broad and open sharing of new biocomputing software.
计算生物学和生物计算领域的大多数被接受的论文都描述了针对相关生物学问题的新软件方法。虽然期刊和会议通常要求提供软件和源代码,但在科学界中,最大化软件的分布和使用的资源是有限的。可接受的标准是在已发表的工作中提供新方法的源代码,但是系统配置问题、语言、库版本冲突和其他实现问题日益严重,这常常阻碍了软件工具的广泛分布、可用性和研究的可重复性。有多种解决方案可以解决这些实现问题,但应用这些解决方案的学习曲线很陡峭。本教程演示了用于发布代码的打包和分发工具和方法,并提供了新的生物计算软件广泛和开放共享的方法实践。