Best practices for conducting benchmarking in the most comprehensive and reproducible way

Computational biology is rapidly advancing thanks to the many new tools developed and published each month. A systematic benchmarking practice would help biomedical researchers leverage this technological expansion to optimize their projects. Several aspects of algorithm publication and distribution contribute to this challenge. We address these challenges and present seven principles to guide researchers in designing a benchmarking study. Our proposed steps show how benchmarking can create a framework for comparison of newly published algorithms.