dPUC

Domain Prediction Using Context

by Alejandro Ochoa García, Manuel Llinás, Mona Singh

Extend your Pfam predictions without loss of precision using domain context!

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dPUC 1.0 is now obsolete!

Please follow the next link to go to the dPUC 2 project page.

dPUC 2
dPUC 2, Domain Prediction Using Context
Extend your Pfam predictions without loss of precision using domain context!
github.com

The old project's page will remain available for historical purposes.

Search predictions

Search our domain predictions on twelve organisms (six Plasmodium species [P. falciparum, P. vivax, P. knowlesi, P. chabaudi, P. berghei, P. yoelii], Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccaromyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis.), and view them graphically, organized by orthology. Search by protein ID, domain names and accessions (Pfam, SMART, and Superfamily), or keywords.

Download predictions

Get our plain text domain and GO term predictions on the twelve test organisms from our publication.

Sequence search

This form performs our dPUC search for Pfam domains on your sequences of choice.

Out of order!!! You will have to download the software to be able to predict domains on your sequences. We apologize for the inconvenience.

Source code

Download our Perl source code, in a gzip-compressed tar archive file.

Citation

2011-03-31. Alejandro Ochoa, Manuel Llinás, Mona Singh. Using context to improve protein domain identification. BMC Bioinformatics. 12:90. PubMed. PubMed Central. Article.

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