InterPro in 2017—beyond protein family and domain annotations
Clicks: 5
ID: 292280
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
1.2
/100
5 views
4 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #515 of 1,217 articles by views in Nucleic Acids Research
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,217 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
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.
| Reference Key |
openalex_W2557496587
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ROBERT FINN, Teresa K. Attwood, Patricia C. Babbitt, Alex Bateman, Peer Bork, Alan Bridge, Hsin-Yu Chang, Zsuzsanna Dosztányi, Sara El-Gebali, Matthew Fraser, Julian Gough, David R Haft, Gemma L. Holliday, Hongzhan Huang, Xiaosong Huang, Ivica Letunić, Rodrigo López, Shennan Lu, Aron Marchler‐Bauer, Huaiyu Mi, Jaina Mistry, Darren A. Natale, Marco Necci, Gift Nuka, Christine Orengo, Young Mi Park, Sebastien Pesseat, Damiano Piovesan, Simon 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 Wu, Ioannis Xénarios, Lai-Su Yeh, Siew-Yit Young, Alex Mitchell |
| Journal | Nucleic Acids Research |
| Year | 2016 |
| DOI |
10.1093/nar/gkw1107
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.