The problem: Traditional curation is not cost-effective and cannot keep up with the constantly increasing rate of publication of novel results

The solution: Assisted curation is a promising avenue to increase the throughput of the curation process without compromising the quality of the results

In our recent paper "Strategies towards digital and semi-automated curation in RegulonDB" we distinguish three level of digital support for database curation:

• Semi-automated curation: a text mining system provides candidate annotations which partially guide the curation process

• Automated curation: higher throughput but lower quality, the user must be informed how the data has been generated

The OntoGene/BioMeXT group has been active in assisted curation since 2010 with the SASEBio project.

Since 2013 we are collaborating with the RegulonDB database in a project aimed at testing and gradually introduce assisted curation techniques in their curation pipeline.
For more details, check the description of our collaboration with RegulonDB.

Please find below the poster presented at ISMB/ECCB 2017.