“…Biomedical text mining is a large field with a wide range of applications such as the automatized extraction of protein–protein interactions [Krallinger et al, 2011], protein mutations [Caporaso et al, 2007; Doughty et al, 2011; Lee et al, 2007; Rebholz‐Schuhmann et al, 2004], pharmacokinetic relationships between genes, drugs, and diseases [Frijters et al, 2010; Garten et al, 2010; Rubin et al, 2005] or protein and gene annotation [Camon et al, 2005]. Several methods have been implemented and applied successfully to mine human kinase mutations [Krallinger et al, 2009], mutations of G‐protein coupled receptors (GPCRs), nuclear hormone receptors (NRs) [Horn et al, 2004], vitamin K‐dependent coagulation serine proteases [Saunders and Perkins, 2008], and α‐galactosidase A mutations related to Fabry disease [Kuipers et al, 2010]. A database that aims to gather protein level enzyme mutations having an effect on protein stability or function from PubMed abstracts is also available [Yeniterzi and Sezerman, 2009].…”