Browsing by Author "Natale, Darren A."
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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.Item Protein Ontology (PRO): enhancing and scaling up the representation of protein entities(Oxford University Press, 2016-11-28) Natale, Darren A.; Arighi, Cecilia N.; Blake, Judith A.; Bona, Jonathan; Chen, Chuming; Chen, Sheng-Chih; Christie, Karen R.; Cowart, Julie; D’Eustachio, Peter; Diehl, Alexander D.; Drabkin, Harold J.; Duncan, William D.; Huang, Hongzhan; Ren, Jia; Ross, Karen; Ruttenberg, Alan; Shamovsky, Veronica; Smith, Barry; Wang, Qinghua; Zhang, Jian; El-Sayed, Abdelrahman; Wu, Cathy H.; Darren A. Natale, Cecilia N. Arighi, Judith A. Blake, Jonathan Bona, Chuming Chen, Sheng-Chih Chen, Karen R. Christie, Julie Cowart, Peter D’Eustachio, Alexander D. Diehl, Harold J. Drabkin, William D. Duncan, Hongzhan Huang, Jia Ren, Karen Ross, Alan Ruttenberg, Veronica Shamovsky, Barry Smith, Qinghua Wang, Jian Zhang, Abdelrahman El-Sayed and Cathy H. Wu; Arighi, Cecilia N.; Chen, Chuming; Chen, Sheng-Chih; Cowart, Julie; Huang, Hongzhan; Ren, Jia; Wang, Qinghua; Wu, Cathy H.The Protein Ontology (PRO; http://purl.obolibrary. org/obo/pr) formally defines and describes taxonspecific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and proteincontaining complexes. PRO thus serves as a tool for referencing protein entities at any level of specificity. To enhance this ability, and to facilitate the comparison of such entities described in different resources, we developed a standardized representation of proteoforms using UniProtKB as a sequence reference and PSI-MOD as a post-translationalmodification reference. We illustrate its use in facilitating an alignment between PRO and Reactome protein entities. We also address issues of scalability, describing our first steps into the use of text mining to identify protein-related entities, the large-scale import of proteoform information from expert curated resources, and our ability to dynamically generate PRO terms. Web views for individual terms are now more informative about closely-related terms, including for example an interactive multiple sequence alignment. Finally, we describe recent improvement in semantic utility, with PRO now represented in OWL and as a SPARQL endpoint. These developments will further support the anticipated growth of PRO and facilitate discoverability of and allow aggregation of data relating to protein entities.Item Toll-Like Receptor Signaling in Vertebrates: Testing the Integration of Protein, Complex, and Pathway Data in the Protein Ontology Framework(Public Library of Science (PLOS), 2015-04-20) Arighi, Cecilia N.; Shamovsky, Veronica; Masci, Anna Maria; Ruttenberg, Alan; Smith, Barry; Natale, Darren A.; Wu, Cathy H.; D’Eustachio, Peter; Cecilia Arighi, Veronica Shamovsky, Anna Maria Masci, Alan Ruttenberg, Barry Smith, Darren A. Natale, Cathy Wu, Peter D’Eustachio; Arighi, Cecilia; Wu, CathyThe Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology and annotation data set has allowed us to identify species-specific gaps in experimental data and possible functional differences between species, and to employ inferred structural and functional relationships to suggest plausible resolutions of these discrepancies and gaps.