What it does
This calls the command line version of the NoD tool from the Barton Group for prediction of nucleolar localization sequences (NoLSs). The NoD tool uses an artificial neural network trained on a set of human NoLSs.
The nucleolus is a sub-compartmentof the nucleus, thus an NoLS can be regarded as a special nuclear localization sequence (NLS).
The input is a FASTA file of protein sequences, and the output is tabular with four columns (multiple rows per protein):
| Column | Description |
| 1 | Sequence identifier |
| 2 | Start of NoLS |
| 3 | End of NoLS |
| 4 | NoLS sequence |
If a sequence has no predicted NoLS, then there is no line in the output file for it.
References
If you use this Galaxy tool in work leading to a scientific publication please cite the following papers:
Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013). Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology. PeerJ 1:e167 https://doi.org/10.7717/peerj.167
M. S. Scott, F. M. Boisvert, M. D. McDowall, A. I. Lamond and G. J. Barton (2010). Characterization and prediction of protein nucleolar localization sequences. Nucleic Acids Research 38(21), 7388-7399. https://doi.org/10.1093/nar/gkq653
M. S. Scott, P. V. Troshin and G. J. Barton (2011). NoD: a Nucleolar localization sequence detector for eukaryotic and viral proteins. BMC Bioinformatics, 12:317. https://doi.org/10.1186/1471-2105-12-317
See also http://www.compbio.dundee.ac.uk/www-nod/
This wrapper is available to install into other Galaxy Instances via the Galaxy Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/clinod