SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P29590 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MEPAPARSPRPQQDPARPQEPTMPPPETPSEGRQPSPSPSPTERAPASEE    50
  51  EFQFLRCQQCQAEAKCPKLLPCLHTLCSGCLEASGMQCPICQAPWPLGAD   100
 101  TPALDNVFFESLQRRLSVYRQIVDAQAVCTRCKESADFWCFECEQLLCAK   150
 151  CFEAHQWFLKHEARPLAELRNQSVREFLDGTRKTNNIFCSNPNHRTPTLT   200
 201  SIYCRGCSKPLCCSCALLDSSHSELKCDISAEIQQRQEELDAMTQALQEQ   250
 251  DSAFGAVHAQMHAAVGQLGRARAETEELIRERVRQVVAHVRAQERELLEA   300
 301  VDARYQRDYEEMASRLGRLDAVLQRIRTGSALVQRMKCYASDQEVLDMHG   350
 351  FLRQALCRLRQEEPQSLQAAVRTDGFDEFKVRLQDLSSCITQGKDAAVSK   400
 401  KASPEAASTPRDPIDVDLPEEAERVKAQVQALGLAEAQPMAVVQSVPGAH   450
 451  PVPVYAFSIKGPSYGEDVSNTTTAQKRKCSQTQCPRKVIKMESEEGKEAR   500
 501  LARSSPEQPRPSTSKAVSPPHLDGPPSPRSPVIGSEVFLPNSNHVASGAG   550
 551  EAEERVVVISSSEDSDAENSSSRELDDSSSESSDLQLEGPSTLRVLDENL   600
 601  ADPQAEDRPLVFFDLKIDNETQKISQLAAVNRESKFRVVIQPEAFFSIYS   650
 651  KAVSLEVGLQHFLSFLSSMRRPILACYKLWGPGLPNFFRALEDINRLWEF   700
 701  QEAISGFLAALPLIRERVPGASSFKLKNLAQTYLARNMSERSAMAAVLAM   750
 751  RDLCRLLEVSPGPQLAQHVYPFSSLQCFASLQPLVQAAVLPRAEARLLAL   800
 801  HNVSFMELLSAHRRDRQGGLKKYSRYLSLQTTTLPPAQPAFNLQALGTYF   850
 851  EGLLEGPALARAEGVSTPLAGRGLAERASQQS                     882

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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