Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 Jul 1;36(Web Server issue):W297-302.
doi: 10.1093/nar/gkn193. Epub 2008 May 7.

FFPred: an integrated feature-based function prediction server for vertebrate proteomes

A E Lobley  1 , T Nugent, C A Orengo, D T Jones
Affiliations

FFPred: an integrated feature-based function prediction server for vertebrate proteomes

A E Lobley et al. Nucleic Acids Res. .

Abstract

One of the challenges of the post-genomic era is to provide accurate function annotations for large volumes of data resulting from genome sequencing projects. Most function prediction servers utilize methods that transfer existing database annotations between orthologous sequences. In contrast, there are few methods that are independent of homology and can annotate distant and orphan protein sequences. The FFPred server adopts a machine-learning approach to perform function prediction in protein feature space using feature characteristics predicted from amino acid sequence. The features are scanned against a library of support vector machines representing over 300 Gene Ontology (GO) classes and probabilistic confidence scores returned for each annotation term. The GO term library has been modelled on human protein annotations; however, benchmark performance testing showed robust performance across higher eukaryotes. FFPred offers important advantages over traditional function prediction servers in its ability to annotate distant homologues and orphan protein sequences, and achieves greater coverage and classification accuracy than other feature-based prediction servers. A user may upload an amino acid and receive annotation predictions via email. Feature information is provided as easy to interpret graphics displayed on the sequence of interest, allowing for back-interpretation of the associations between features and function classes.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Server process flow diagram.
Figure 2.
Figure 2.
Sample output from the server for sequence IPI00745501.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Ofran Y, Punta M, Schneider R, Rost B. Beyond annotation transfer by homology: novel protein function prediction methods to assist drug discovery. Drug Discov. Today. 2005;10:1475–1482. - PubMed
    1. Rost B. Enzyme function less conserved than anticipated. J. Mol. Biol. 2002;318:595–608. - PubMed
    1. Tian W, Skolnick J. How well is enzyme function conserved as a function of pairwise sequence identity? 2003;333:863–882. - PubMed
    1. Dobson PD, Doig AJ. Predicting enzyme class from protein structure without alignments. 2004;345:187–199. - PubMed
    1. Jensen LJ, Stærfeldt H-H, Brunak S. Prediction of human protein function according to Gene Ontology categories. Bioinformatics. 2003;19:635–642. - PubMed

Publication types