Toward Computer-Assisted Text Curation: Classification Is Easy (Choosing Training Data Can Be Hard...).

We aim to design a system for classifying scientific articles based on the presence of protein characterization experiments, intending to aid the curators populating JCVI΄s Characterized Protein (CHAR) Database of experimentally characterized proteins. We trained two classifiers using small datasets labeled by CHAR curators, and another classifier based on a much larger dataset using annotations from public databases. Performance varied greatly, in ways we did not anticipate. We describe the datasets, the classification method, and discuss the unexpected results. [ABSTRACT FROM AUTHOR]