ReRank allows you to rank your pubmed search results based on the impact they have had. This allows you to see which of the articles have produced the most discussion, been cited the most or have been recommended by academics.
ReRank was built in a hackbreak at the Altmetrics Hackathon on Nov 3, 2012 at PLOS in San Francisco.
The ranking is based on data provided by the ImpactStory API. ImpactStory aggregates altmetrics: diverse impacts from your articles, datasets, blog posts, and more.
The source code for ReRank can be found on github here. To use ReRank, drag the following into your bookmarks toolbar, 
and click it while searching on pubmed.
