Evidence map›Paper›PMID 25964299›Full record

ArticleNucleic acids research2015

CATH FunFHMMer web server: protein functional annotations using functional family assignments.

Sayoni Das, Ian Sillitoe, David Lee, Jonathan G Lees, Natalie L Dawson, John Ward, Christine A Orengo

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

  1. Article
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  4. Clustering protein functional families at large scale with hierarchical approaches.Protein science : a publication of the Protein Society · 2024
    Article
  5. Article
  6. Article
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  11. Three-dimensional Structure Databases of Biological Macromolecules.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  12. Article
  13. Article
  14. Heterologous expression of cyanobacterialPlant biotechnology reports · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sayoni DasInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK sayoni.das.12@ucl.ac.uk.
Ian SillitoeInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK i.sillitoe@ucl.a.uk.
David LeeInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK.
Jonathan G LeesInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK.
Natalie L DawsonInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK.
John WardDepartment of Biochemical Engineering, UCL, Gower Street, WC1E 6BT, UK.
Christine A OrengoInstitute of Structural and Molecular Biology, UCL, Darwin Building, Gower Street, WC1E 6BT, UK c.orengo@ucl.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/K020013/1Biotechnology and Biological Sciences Research Council BB/L002817/1Wellcome Trust 081989/Z/07/Z
6 · The paper itself

Abstract

The widening function annotation gap in protein databases and the increasing number and diversity of the proteins being sequenced presents new challenges to protein function prediction methods. Multidomain proteins complicate the protein sequence-structure-function relationship further as new combinations of domains can expand the functional repertoire, creating new proteins and functions. Here, we present the FunFHMMer web server, which provides Gene Ontology (GO) annotations for query protein sequences based on the functional classification of the domain-based CATH-Gene3D resource. Our server also provides valuable information for the prediction of functional sites. The predictive power of FunFHMMer has been validated on a set of 95 proteins where FunFHMMer performs better than BLAST, Pfam and CDD. Recent validation by an independent international competition ranks FunFHMMer as one of the top function prediction methods in predicting GO annotations for both the Biological Process and Molecular Function Ontology. The FunFHMMer web server is available at http://www.cathdb.info/search/by_funfhmmer.

Indexed as

Molecular Sequence AnnotationProtein Structure, TertiarySoftwareGene OntologyInternetProteinsProteins

Identifiers

PMID25964299
PMCPMC4489299

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.