Name
Abstract | ||
|---|---|---|
SH3-Hunter (http://cbm.bio.uniroma2.it/SH3Hunter/) is a web server for the recognition of putative SH3 domain interaction sites on protein sequences. Given an input query consisting of one or more protein sequences, the server identifies peptides containing poly-proline binding motifs and associates them to a list of SH3 domains, in order to compose peptide-domain pairs. The server can accept a list of peptides and allows users to upload an input file in a proper format. An accurate selection of SH3 domains is available and users can also submit their own SH3 domain sequence. SH3-Hunter evaluates which peptide-domain pair represents a possible interaction pair and produces as output a list of significant interaction sites for each query protein. Each proposed interaction site is associated to a propensity score and sensitivity and precision levels for the prediction. The server prediction capability is based on a neural network model integrating high-throughput pep-spot data with structural information extracted from known SH3-peptide complexes. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1093/nar/gkm296 | NUCLEIC ACIDS RESEARCH |
Keywords | Field | DocType |
computational biology,propensity score,high throughput,neural network model,information extraction,nucleic,sh3 domain,protein sequence,amino acid sequence,protein binding,binding sites | Protein domain,Information retrieval,Biology,Upload,Amino Acid Motifs,Bioinformatics,Genetics,SH3 domain,Artificial neural network,Peptide sequence,Web server | Journal |
Volume | Issue | ISSN |
35 | SUPnan | 0305-1048 |
Citations | PageRank | References |
2 | 0.38 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrico Ferraro | 1 | 42 | 2.16 |
| Daniele Peluso | 2 | 475 | 22.09 |
| Allegra Via | 3 | 616 | 44.62 |
| Gabriele Ausiello | 4 | 301 | 23.59 |
| Manuela Helmer-Citterich | 5 | 456 | 33.41 |