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

NucPred

Fetching Q15021 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MAPQMYEFHLPLSPEELLKSGGVNQYVVQEVLSIKHLPPQLRAFQAAFRA    50
  51  QGPLAMLQHFDTIYSILHHFRSIDPGLKEDTLQFLIKVVSRHSQELPAIL   100
 101  DDTTLSGSDRNAHLNALKMNCYALIRLLESFETMASQTNLVDLDLGGKGK   150
 151  KARTKAAHGFDWEEERQPILQLLTQLLQLDIRHLWNHSIIEEEFVSLVTG   200
 201  CCYRLLENPTINHQKNRPTREAITHLLGVALTRYNHMLSATVKIIQMLQH   250
 251  FEHLAPVLVAAVSLWATDYGMKSIVGEIVREIGQKCPQELSRDPSGTKGF   300
 301  AAFLTELAERVPAILMSSMCILLDHLDGENYMMRNAVLAAMAEMVLQVLS   350
 351  GDQLEAAARDTRDQFLDTLQAHGHDVNSFVRSRVLQLFTRIVQQKALPLT   400
 401  RFQAVVALAVGRLADKSVLVCKNAIQLLASFLANNPFSCKLSDADLAGPL   450
 451  QKETQKLQEMRAQRRTAAASAVLDPEEEWEAMLPELKSTLQQLLQLPQGE   500
 501  EEIPEQIANTETTEDVKGRIYQLLAKASYKKAIILTREATGHFQESEPFS   550
 551  HIDPEESEETRLLNILGLIFKGPAASTQEKNPRESTGNMVTGQTVCKNKP   600
 601  NMSDPEESRGNDELVKQEMLVQYLQDAYSFSRKITEAIGIISKMMYENTT   650
 651  TVVQEVIEFFVMVFQFGVPQALFGVRRMLPLIWSKEPGVREAVLNAYRQL   700
 701  YLNPKGDSARAKAQALIQNLSLLLVDASVGTIQCLEEILCEFVQKDELKP   750
 751  AVTQLLWERATEKVACCPLERCSSVMLLGMMARGKPEIVGSNLDTLVSIG   800
 801  LDEKFPQDYRLAQQVCHAIANISDRRKPSLGKRHPPFRLPQEHRLFERLR   850
 851  ETVTKGFVHPDPLWIPFKEVAVTLIYQLAEGPEVICAQILQGCAKQALEK   900
 901  LEEKRTSQEDPKESPAMLPTFLLMNLLSLAGDVALQQLVHLEQAVSGELC   950
 951  RRRVLREEQEHKTKDPKEKNTSSETTMEEELGLVGATADDTEAELIRGIC  1000
1001  EMELLDGKQTLAAFVPLLLKVCNNPGLYSNPDLSAAASLALGKFCMISAT  1050
1051  FCDSQLRLLFTMLEKSPLPIVRSNLMVATGDLAIRFPNLVDPWTPHLYAR  1100
1101  LRDPAQQVRKTAGLVMTHLILKDMVKVKGQVSEMAVLLIDPEPQIAALAK  1150
1151  NFFNELSHKGNAIYNLLPDIISRLSDPELGVEEEPFHTIMKQLLSYITKD  1200
1201  KQTESLVEKLCQRFRTSRTERQQRDLAYCVSQLPLTERGLRKMLDNFDCF  1250
1251  GDKLSDESIFSAFLSVVGKLRRGAKPEGKAIIDEFEQKLRACHTRGLDGI  1300
1301  KELEIGQAGSQRAPSAKKPSTGSRYQPLASTASDNDFVTPEPRRTTRRHP  1350
1351  NTQQRASKKKPKVVFSSDESSEEDLSAEMTEDETPKKTTPILRASARRHR  1400
1401  S                                                   1401

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.)

Go back to the NucPred Home Page.