The Protein Information Resource
By Cathy H. Wu, L. Yeh, Hongzhan Huang, L. Arminski, Jorge Castro-Alvear, Yongxing Chen, Zhang-Zhi Hu, P. Kourtesis, R. Ledley, Baris E. Suzek and 3 more. Nucleic Acids Res., 2003
471 citations recorded by the source corpus.
The Protein Information Resource (PIR) is an integrated public resource of protein informatics that supports genomic and proteomic research and scientific discovery. PIR maintains the Protein Sequence Database (PSD), an annotated protein database containing over 283 000 sequences covering the entire taxonomic range. Family classification is used for sensitive identification, consistent annotation, and detection of annotation errors. The superfamily curation defines signature domain architecture and categorizes memberships to improve automated classification. To increase the amount of experimental annotation, the PIR has developed a bibliography system for literature searching, mapping, and user submission, and has conducted retrospective attribution of citations for experimental features. PIR also maintains NREF, a non-redundant reference database, and iProClass, an integrated database of protein family, function, and structure information. PIR-NREF provides a timely and comprehensive collection of protein sequences, currently consisting of more than 1 000 000 entries from PIR-PSD, SWISS-PROT, TrEMBL, RefSeq, GenPept, and PDB. The PIR web site (http://pir.georgetown.edu) connects data analysis tools to underlying databases for information retrieval and knowledge discovery, with functionalities for interactive queries, combinations of sequence and text searches, and sorting and visual exploration of search results. The FTP site provides free download for PSD and NREF biweekly releases and auxiliary databases and files.
Subfields: Molecular Biology, Spectroscopy
View Paper: https://www.semanticscholar.org/paper/f9be06d828f4fb334ce6168983528d4a7afcd9ef
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Burkhard Rost
- Vladimir N Uversky
- A. Keith Dunker
- Christopher J. Oldfield
- Stephen H. Bryant
- Predrag Radivojac
- Lukasz Kurgan
- Andrej Sali
In Spectroscopy
- Burkhard Rost
- Stephen H. Bryant
- Weizhong Li
- Adam Godzik
- Evan E. Bolton
- Lukasz Jaroszewski
- Vladimir N Uversky
- Cathy H. Wu
Citations in the corpus
- ProTherm and ProNIT: thermodynamic databases for proteins and protein–nucleic acid interactions (2005, background): “The ProTherm page also provides cross-reference tables necessary for creating cross-links with PDB (10), PIR ( 11 )”
- UniProt: the Universal Protein knowledgebase (2004, methodology): “NREF database ( 2 ), a comprehensive non-redundant sequence collection clustered by sequence identity and taxonomy with source attribution.”
- The Sorcerer II Global Ocean Sampling Expedition: Expanding the Universe of Protein Families (2007, background): “NCBI-nr [31,32] is the single largest publicly available protein resource and includes protein sequences submitted to SWISS-PROT (curated protein database) [122], PDB (a database of amino acid sequences with solved structures) [123], PIR (Protein Information Resource) [124], and PRF (Protein Researc”
- PIRSF: family classification system at the Protein Information Resource (2004, background): “We have also enhanced iProClass (3), an integrated database of protein family, function and structure information with executive summaries and cross-references to over 50 molecular databases; maintained PIR-NREF (4), a non-redundant reference database; and improved the PIR website for scienti®c inqu”
- Analysis of molecular recognition features (MoRFs). (2006, methodology): “Using other database references (Swiss-Prot, 97 PIR, 98 and NCBI referenced in the respective PDB files for each of the MoRF sequences) we were able to extract 301 sequences containing these 372 MoRF chains.”
- A tissue-specific atlas of mouse protein phosphorylation and expression. (2010, unknown): “, 2000) and PIR classifications (Wu et al., 2003) were then clustered based on p values reflecting enrichment in each class, following log transformation and z-transformation (Figure S5).”
- DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis (2007, methodology): “Some integrated databases, such as NCBI Entrez Gene [1], UniProt [2], PIR [3], etc., made great efforts to integrate annotation resources in one centralized location and are considered to be the world-class bioinformatics foundation for general bioinformatics purposes.”
- Database resources of the National Center for Biotechnology Information (2010, background): “In addition to these 23 million ‘GenPept’ sequences, the Protein database also contains sequences from TPA, SWISSPROT (11), the Protein Information Resource (PIR) (12), the Protein Research Foundation (PRF) and the Protein Data Bank (PDB) (13).”
- A fast Peptide Match service for UniProt Knowledgebase (2013, background): “The Peptide Match service is designed to quickly retrieve all occurrences of a given query peptide from UniProt Knowledgebase (UniProtKB) with isoforms.”
- Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists (2008, unknown): “Even though the identifier cross-mapping issues were effectively addressed within each major bioinformatics organization, such as NCBI Entrez Gene (89), UniProt UniRef (90) and PIR-NREF (91), respectively, the weaker referencing capability across organizations still exists.”
- The Universal Protein Resource (UniProt) (2004, background): “The UniProt Knowledgebase merges Swiss-Prot, TrEMBL and PIR-PSD to provide a central database of protein sequences with annotations and functional information.”