BIOS 261: Rigor and reproducibility in biological research: collection, analysis and use of biological data

Biosciences Interdisciplinary Stanford University 2.0 credits

Course Description

The deluge of data common in modern biological research poses new challenges for ensuring reproducibility and collaboration at many levels. High-powered computational and statistical tools are becoming as indispensable as pipettes and flasks, demanding a rethinking of what it means to be rigorous and reproducible in the generation, visualization, and interpretation of results. In this mini-course, we will explore key concepts in how data should be stored, analyzed, manipulated, and presented using computational tools such as the Python programming language and GitHub version control software at a hands-on level, guiding students through a mini research project. This is an introductory course that assumes no previous knowledge of programming or statistics, and is especially relevant for students or postdocs interested in developing a skill set for quantitative biology.

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