Robert D. Finn 1 , * , Teresa K. Attwood 2 , Patricia C. Babbitt 3 , Alex Bateman 1 , Peer Bork 4 , Alan J. Bridge 5 , Hsin-Yu Chang 1 , Zsuzsanna Dosztányi 6 , Sara El-Gebali 1 , Matthew Fraser 1 , Julian Gough 7 , David Haft 8 , Gemma L. Holliday 3 , Hongzhan Huang 9 , Xiaosong Huang 10 , Ivica Letunic 11 , Rodrigo Lopez 1 , Shennan Lu 12 , Aron Marchler-Bauer 12 , Huaiyu Mi 10 , Jaina Mistry 1 , Darren A. Natale 13 , Marco Necci 14 , Gift Nuka 1 , Christine A. Orengo 15 , Youngmi Park 1 , Sebastien Pesseat 1 , Damiano Piovesan 14 , Simon C. Potter 1 , Neil D. Rawlings 1 , Nicole Redaschi 5 , Lorna Richardson 1 , Catherine Rivoire 5 , Amaia Sangrador-Vegas 1 , Christian Sigrist 5 , Ian Sillitoe 15 , Ben Smithers 7 , Silvano Squizzato 1 , Granger Sutton 8 , Narmada Thanki 12 , Paul D Thomas 10 , Silvio C. E. Tosatto 14 , 16 , Cathy H. Wu 9 , Ioannis Xenarios 5 , Lai-Su Yeh 13 , Siew-Yit Young 1 , Alex L. Mitchell 1
28 November 2016
InterPro ( http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences.