Publish your computer code: it is good enough

By Nick Barnes. Nature, 2010

315 citations recorded by the source corpus.

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phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data (2013, background): “We emphasize that the benefits of reproducibility are not contingent on ‘‘pretty’’ code [87], and we encourage researchers in the field to make their code available even if they feel insecure about its programmatic elegance.”
Mechanistic simulation models in macroecology and biogeography: state‐of‐art and prospects (2017, methodology): “To maximize the potential and use of mechanistic models, collaborative approaches should be strengthened, for example by code sharing (Barnes 2010) and the provision of adequate software and user interfaces (e.g.”
Ten quick tips for machine learning in computational biology (2017, background): “] enables others to engage with your research” [60].”
Evaluation of TanDEM-X DEMs on selected Brazilian sites: Comparison with SRTM, ASTER GDEM and ALOS AW3D30 (2017, methodology): “In order to streamline the process and ensure reproducibility (Barnes, 2010), data processing was performed in GRASS-GIS version 7.2 (Neteler et al., 2012; GRASS Development Team, 2017) through Python scripts (Python Software Foundation, 2013) using the Pygrass library (Zambelli et al., 2013) to…”