The in silico lab: Improving academic code using lessons from biology.

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jason Y Cain, Jessica S Yu, Neda Bagheri
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引用次数: 0

Abstract

"Good code" is often regarded as a nebulous, impractical ideal. Common best practices toward improving code quality can be inaccessible to those without a rigorous computer science or software engineering background, contributing to a gap between advancing scientific research and FAIR practices. We seek to equip researchers with the necessary background and context to tackle the challenge of improving code quality in computational biology research using analogies from biology to synthesize why certain best practices are critical for advancing computational research. Improving code quality requires active stewardship; we encourage researchers to deliberately adopt and share practices that ensure reusability, repeatability, and reproducibility.

计算机实验室:利用生物学的经验改进学术代码。
“好的代码”通常被认为是一个模糊的、不切实际的理想。对于那些没有严格的计算机科学或软件工程背景的人来说,提高代码质量的通用最佳实践可能是不可接近的,这导致了推进科学研究和公平实践之间的差距。我们试图为研究人员提供必要的背景和背景,以解决在计算生物学研究中提高代码质量的挑战,使用生物学的类比来综合为什么某些最佳实践对推进计算研究至关重要。提高代码质量需要积极的管理;我们鼓励研究人员有意识地采用和分享确保可重用性、可重复性和可再现性的实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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