The ERPIN server: an interface to profile-based RNA motif identification
CNRS UMR 6207 and 1 INSERM ERM 206, Université de la Méditerranée, Luminy Case 906, 13288 Marseille, Cedex 09, France, 2 UMR 7567 CNRS-UHP, Université Henri Poincaré, 54506 Vandoeuvre-lès-Nancy cedex, France, 3 Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, CP 6128, Succ. Centre-Ville, Montréal, Québec, Canada H3C 3J7, 4 CNRS UPR 9073, 13 rue P. et M. Curie, 75005 Paris, France and 5 ACTiGenics, 10 avenue de l'Europe, 31525 Ramonville St Agne, France
* To whom correspondence should be addressed. Tel: +33 491 828639; Fax: +33 491 828621; Email: gautheret{at}esil.univ-mrs.fr
Present address: Jean-Fred Fontaine, INSERM EMI U 00.18, CHU d'Angers, 49033 Angers, France
Received February 13, 2004; Revised and Accepted April 5, 2004
ERPIN is an RNA motif identification program that takes an RNA sequence alignment as an input and identifies related sequences using a profile-based dynamic programming algorithm. ERPIN differs from other RNA motif search programs in its ability to capture subtle biases in the training set and produce highly specific and sensitive searches, while keeping CPU requirements at a practical level. In its latest version, ERPIN also computes E-values, which tell biologists how likely they are to encounter a specific sequence match by chance—a useful indication of biological significance. We present here the ERPIN online search interface (http://tagc.univ-mrs.fr/erpin/). This web server automatically performs ERPIN searches for different RNA genes or motifs, using predefined training sets and search parameters. With a couple of clicks, users can analyze an entire bacterial genome or a genomic segment of up to 5Mb for the presence of tRNAs, 5S rRNAs, SRP RNA, C/D box snoRNAs, hammerhead motifs, miRNAs and other motifs. Search results are displayed with sequence, score, position, E-value and secondary structure graphics. An example of a complete genome scan is provided, as well as an evaluation of run times and specificity/sensitivity information for all available motifs.
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  C. Pichon and B. Felden Small RNA gene identification and mRNA target predictions in bacteria Bioinformatics, December 15, 2008; 24(24): 2807 - 2813. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. St-Onge, P. Thibault, S. Hamel, and F. Major Modeling RNA tertiary structure motifs by graph-grammars Nucleic Acids Res., March 27, 2007; (2007) gkm069v2. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. D. Baird, M. Turcotte, R. G. Korneluk, and M. Holcik Searching for IRES RNA, October 1, 2006; 12(10): 1755 - 1785. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. de la Grange, M. Dutertre, N. Martin, and D. Auboeuf FAST DB: a website resource for the study of the expression regulation of human gene products Nucleic Acids Res., July 28, 2005; 33(13): 4276 - 4284. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Legendre, A. Lambert, and D. Gautheret Profile-based detection of microRNA precursors in animal genomes Bioinformatics, April 1, 2005; 21(7): 841 - 845. [Abstract] [Full Text] [PDF]
|
|