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UniProt: a hub for protein information.

- Nucleic Acids Res. (2014)

Bottom Line: We present a new website that has been designed using a user-experience design process.We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein.These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis.

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Growth of coverage of UniProtKB/TrEMBL by manually curated UniRules. The Y-axis shows the percentage coverage of UniProtKB/TrEMBL by UniRule as a whole as well as by the individual sources. PIR represents the combination of both PIR Site Rules (PIRSR) and PIR Name Rules (PIRNR).
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Figure 5: Growth of coverage of UniProtKB/TrEMBL by manually curated UniRules. The Y-axis shows the percentage coverage of UniProtKB/TrEMBL by UniRule as a whole as well as by the individual sources. PIR represents the combination of both PIR Site Rules (PIRSR) and PIR Name Rules (PIRNR).

Mentions: The coverage of UniProtKB/TrEMBL has grown from 28% to 35% over the last 4 years despite the exponential increase in the size of the database, see Figure 5. This is due in part to a large amount of the increase being the result of the integration of redundant complete bacterial proteomes, which have been annotated by our existing UniRules for bacteria. Our strategy for addressing this redundancy will be discussed in the proteome section in this paper. Our automatic annotation priorities for UniRule generation are (i) to focus on using and annotating new functional data of interest for proteomes, such as enzymes and pathways and (ii) to expand our coverage into new taxonomic and protein families and (iii) to expand the scope of annotations by leveraging curated data via collaboration with external groups, as is the case with post-translational modification (PTM) data in RESID database (as an example see UniRule annotation of (UniProt F2I0T3) in the PTM/Processing section, with rule information based on RESID:AA0120).


UniProt: a hub for protein information.

- Nucleic Acids Res. (2014)

Growth of coverage of UniProtKB/TrEMBL by manually curated UniRules. The Y-axis shows the percentage coverage of UniProtKB/TrEMBL by UniRule as a whole as well as by the individual sources. PIR represents the combination of both PIR Site Rules (PIRSR) and PIR Name Rules (PIRNR).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4384041&req=5

Figure 5: Growth of coverage of UniProtKB/TrEMBL by manually curated UniRules. The Y-axis shows the percentage coverage of UniProtKB/TrEMBL by UniRule as a whole as well as by the individual sources. PIR represents the combination of both PIR Site Rules (PIRSR) and PIR Name Rules (PIRNR).
Mentions: The coverage of UniProtKB/TrEMBL has grown from 28% to 35% over the last 4 years despite the exponential increase in the size of the database, see Figure 5. This is due in part to a large amount of the increase being the result of the integration of redundant complete bacterial proteomes, which have been annotated by our existing UniRules for bacteria. Our strategy for addressing this redundancy will be discussed in the proteome section in this paper. Our automatic annotation priorities for UniRule generation are (i) to focus on using and annotating new functional data of interest for proteomes, such as enzymes and pathways and (ii) to expand our coverage into new taxonomic and protein families and (iii) to expand the scope of annotations by leveraging curated data via collaboration with external groups, as is the case with post-translational modification (PTM) data in RESID database (as an example see UniRule annotation of (UniProt F2I0T3) in the PTM/Processing section, with rule information based on RESID:AA0120).

Bottom Line: We present a new website that has been designed using a user-experience design process.We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein.These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis.

View Article: PubMed Central - PubMed

Show MeSH
Related in: MedlinePlus