What it does
This calls the NLStradamus tool for prediction of nuclear localization signals (NLSs), which uses a Hidden Markov Model (HMM).
The input is a FASTA file of protein sequences, and the output is tabular with six columns (one row per NLS):
| Column | Description |
| c1 | Sequence identifier |
| c2 | Algorithm (posterior or Viterbi) |
| c3 | Score (probability between threshold and 1 for posterior algorithm) |
| c4 | Start |
| c5 | End |
| c6 | Sequence of NLS |
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 http://dx.doi.org/10.7717/peerj.167
A. N. Nguyen Ba, A. Pogoutse, N. Provart, A. M. Moses (2009). NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction. BMC Bioinformatics 10(1):202. http://dx.doi.org/10.1186/1471-2105-10-202
See also http://www.moseslab.csb.utoronto.ca/NLStradamus
This wrapper is available to install into other Galaxy Instances via the Galaxy Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/nlstradamus