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

NucPred

Fetching Q2QL74 from www.uniprot.org...

The NucPred score for your sequence is 0.60 (see score help below)

   1  MQRSPLEKANFLSKLFFSWTRPILRKGFRQRLELSDIYQIPLSNSADYLS    50
  51  ENLEREWDRELASKKKPKLINALRRCFFWRFVFHGIILYLGEVTKAVQPL   100
 101  LLGRIIASYDPDNKVERSIAIYLGIGLCLLFIVRTLLLHPAIFGLHHMGM   150
 151  QMRIALFSLIYKKTLKLSSRVLDKISTGQLISLLSNNLNKFDEGLALAHF   200
 201  VWIVPLQVVLLMGLLWDLLQASAFCGLAFLIVLALFQAWLGQMMMKYRER   250
 251  RAGKINERLVITSEMIDNIQSVKAYCWEEAMEKMIENLRETELKLTRKTA   300
 301  YVRYFNSSAFFFSGFFVVFLAVLPYALIKGIILRKIFTTISFCIVLRMAV   350
 351  TRQFPWAVQTWYDSLGAINKIQDFLQKEEYKTLEYNLTTTDVVMENITAF   400
 401  WDEGFGELFVKAKQNNSDVKMSNGDNGLFFSNFSLLGTPVLKNISFKIEK   450
 451  GQLLAVAGSTGAGKTSLLMMIMGELEPSEGKIKHSGRISFCSQFSWIMPG   500
 501  TIKENIIFGVSYDEYRYRSVIKACQLEEDISKFAEKDNTVLGEGGITLSG   550
 551  GQRARISLARAIYKDADLYLLDSPFGYLDVLTEKEIFESCVCKLMANKTR   600
 601  ILITSKMEHLKKADKILILHEGSCYFYGAFSELQNLRPDFSSKLMGYDSF   650
 651  DQFSAERRSSILTETLRRFSIEGDTAVSWNEGKKQSFKQTGDFGERRKNS   700
 701  ILNPLNSIRKFSVVQKGQPQMNGIEENDDEPLERRLSLVPDSEQGEAILP   750
 751  RSNIINTGPTFQGRNRRQSVLNLMTRPSISQGQNMFKTGNAARKMSMAPQ   800
 801  SKLSEIDIYSRRLSQDSGMDISDEINEEDLKEWFFDDVENIPAVTTWNTY   850
 851  LRYITIHKNLVFVLIWCLVIFLVEVAASLVGLWLLEDISFKDKTNGTNGA   900
 901  NNTFPVIITDTSKYYLFYIYVGIADTFFALGIFRGLPLVHTLISVSKILH   950
 951  HKMLYSVLKAPMSTFNTLKPGGILNRFSKDIAILDDLLPLTIFDFIQLIL  1000
1001  IVVGALIVVSAIRPYIFLATVPVIIAFIMLRAYFLQTSQQLKQLESEART  1050
1051  PIFTHLVTSLKGLWTLRAFGRQPYFETLFHKALNLHTASWFLYLSTLRWF  1100
1101  QMRIELVFVIFFIAVTFISILTTGDGEGRVGILLTLAMNIMSTLQWAVNS  1150
1151  SIDVDSLMRSVSRVFKFIDMPTEEPLPAKPTKSLKKNQLSQVLIIENEHV  1200
1201  NKENNWPSGGQMIVKDLTAKYTDGGNAVLENISFSISPGQRVGLLGRTGS  1250
1251  GKSTLLAAFLRLLNTEGEMQIDGVSWDSIPLQKWRKAFGVIPQKVFIFSG  1300
1301  TFRKNLDPYGQWSDHELWKVADEVGLKSVIEQFPGKLDFVLVDGGYVLSH  1350
1351  GHKQLICLARSVLSKAKILLLDEPSAHLDPITYQIIRRVLKNAFANCTVI  1400
1401  LSEHRIEAMLECQRFLVIEDNKVRQYESIQKLVNEKSLYRQAISHSDRMK  1450
1451  LFPHRNSSRHKSLAKITALKEETEEEVQETRL                    1482

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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