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

NucPred

Fetching Q949G3 from www.uniprot.org...

The NucPred score for your sequence is 0.34 (see score help below)

   1  MEPADLSNLRGRSLRASIRGSMRGSIRENSNSIWRNNGAEVFSRSARDED    50
  51  DEEALKWAALEKLPTYDRLRKGILFGSQGAAAEVDVDDSGVLERKNLLER   100
 101  LVKVADEDNEKFLLKLKNRIDRVGIDFPSIEVRFEHLNIDADAYVGSRAL   150
 151  PTFTNFISNFVEGLLDSIHILPSKKRQVTILKDVSGIVKPCRMTLLLGPP   200
 201  GSGKTTLLLALAGKLDSALKVTGKVTYNGHELHEFVPQRTAAYISQHDLH   250
 251  IGEMTVRETLEFSARCQGVGSRYEMLAELSRREKAANIKPDADIDMFMKA   300
 301  ASTEGQEAKVVTDYILKILGLDICADTMVGDQMIRGISGGQKKRVTTGEM   350
 351  IVGPSKALFMDEISTGLDSSTTYSIVNSLKQSVRIMKGTALISLLQPAPE   400
 401  TYNLFDDIILLSDGYIVYEGPREEVLEFFESMGFKCPERKGAADFLQEVT   450
 451  SKKDQQQYWIRRDEPYRFITSKEFAEAYQSFHVGRKVSDELKTTFDKSKS   500
 501  HPAALTTQKYGIGKRQLLKVCTERELLLMQRNSFVYLFKFFQLLIIALMT   550
 551  MTIFFRTKMPRDSAEDGGIYSGALFFVVIMIMFNGLSELPMTLYKLPVFY   600
 601  KQRDFLFYPSWAYAIPSWILKIPVTFAEVGMWVFLTYYVMGFDPNVGRFF   650
 651  KQFLLLLLVNQMASALFRFIAAVGRTMGVASTFGAFALLLQFALGGFILA   700
 701  RNDVKDWWIWGYWTSPLMYSVNAILVNEFDGQKWKHIVAGGTEPLGAAVV   750
 751  RARGFFPDAYWYWIGVGALAGFIVMFNIAYSVALAYLNPFDKPQATISDE   800
 801  SENNESESSPQITSTQEGDSASENKKKGMVLPFDPHSITFDEVVYSVDMP   850
 851  PEMRESGTSDNRLVLLKSVSGAFRPGVLTALMGVSGAGKTTLMDVLAGRK   900
 901  TGGYIDGSIKISGYPKKQDTFARISGYCEQNDIHSPYVTVFESLVYSAWL   950
 951  RLPQDVNEEKRMMFVEEVMDLVELTPLRSALVGLPGVNGLSTEQRKRLTI  1000
1001  AVELVANPSIIFMDEPTSGLDARAAAIVMRAVRNTVDTGRTVVCTIHQPS  1050
1051  IDIFEAFDELFLMKRGGQEIYVGPLGRQSCHLIKYFESIPGVSKIVEGYN  1100
1101  PATWMLEVTASSQEMALGVDFTDLYKKSDLYRRNKALIDELSVPRPGTSD  1150
1151  LHFDSEFSQPFWTQCMACLWKQHWSYWRNPAYTAVRLIFTTFIALIFGTM  1200
1201  FWDIGTKVSRNQDLVNAMGSMYAAVLFLGVQNSSSVQPVVSVERTVFYRE  1250
1251  KAAGMYSAIPYAFAQVLIEIPYIFVQATVYGLIVYSMIGFEWTVAKFFWD  1300
1301  FFFMFFTFLYFTFFGMMTVAVTPNQNVASIVAGFFYTVWNLFSGFIVPRP  1350
1351  RIPIWWRWYYWGCPIAWTLYGLVASQFGDLQDPLTDQNQTVEQFLRSNFG  1400
1401  FKHDFLGVVAAVIVAFAVVFAFTFALGIKAFNFQRR                1436

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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