Browsing by Author "Babbitt, Patricia C."
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Item InterPro in 2017––beyond protein family and domain annotations(Oxford University Press, 2016-11-28) Finn, Robert D.; Attwood, Teresa K.; Babbitt, Patricia C.; Bateman, Alex; Bork, Peer; Bridge, Alan J.; Chang, Hsin-Yu; Doszt´anyi, Zsuzsanna; El-Gebali, Sara; Fraser, Matthew; Gough, Julian; Haft, David; Holliday, Gemma L.; Huang, Hongzhan; Huang, Xiaosong; Letunic, Ivica; Lopez, Rodrigo; Lu, Shennan; Marchler-Bauer, Aron; Mi, Huaiyu; Mistry, Jaina; Natale, Darren A.; Necci, Marco; Nuka, Gift; Orengo, Christine A.; Park, Youngmi; Pesseat, Sebastien; Piovesan, Damiano; Potter, Simon C.; Rawlings, Neil D.; Redaschi, Nicole; Richardson, Lorna; Rivoire, Catherine; Sangrador-Vegas, Amaia; Sigrist, Christian; Sillitoe, Ian; Smithers, Ben; Squizzato, Silvano; Sutton, Granger; Thanki, Narmada; Thomas, Paul D.; Tosatto, Silvio C. E.; Wu, Cathy H.; Xenarios, Ioannis; Yeh, Lai-Su; Young, Siew-Yit; Mitchell, Alex L.; Robert D. Finn, Teresa K. Attwood, Patricia C. Babbitt, Alex Bateman, Peer Bork, Alan J. Bridge, Hsin-Yu Chang, Zsuzsanna Doszt´anyi, Sara El-Gebali, Matthew Fraser, Julian Gough, David Haft, Gemma L. Holliday, Hongzhan Huang, Xiaosong Huang, Ivica Letunic, Rodrigo Lopez, Shennan Lu, Aron Marchler-Bauer, Huaiyu Mi, Jaina Mistry, Darren A Natale, Marco Necci, Gift Nuka, Christine A. Orengo, Youngmi Park, Sebastien Pesseat, Damiano Piovesan, Simon C. Potter, Neil D. Rawlings, Nicole Redaschi, Lorna Richardson, Catherine Rivoire, Amaia Sangrador-Vegas, Christian Sigrist, Ian Sillitoe, Ben Smithers, Silvano Squizzato, Granger Sutton, Narmada Thanki, Paul D Thomas, Silvio C. E. Tosatto, Cathy H.Wu, Ioannis Xenarios, Lai-Su Yeh, Siew-Yit Young and Alex L. Mitchell; Wu, Cathy H.; Huang, HongzhanInterPro (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 Inter- Pro’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.