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How to make your research reproducible (5 selfish reasons to work reproducibly)

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There is increasing realisation that for publications to have maximum impact, the findings must be replicated and expanded by others. Technological advances in all areas of the life sciences now require increasingly complex data analyses. It can become difficult to keep track of one’s own analysis workflow, let alone expect others to repeat the same analysis later. Moreover, there have been high-profile cases where clinical decisions have been based on flawed and misleading analyses. The speakers will describe technologies that can help us be more reproducible and share their own successes and failures in satisfying journal requirements for transparent analyses.

This talk is part of the "Life Sciences Masterclass" series.

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