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

NucPred

Fetching P70211 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MENSLGCVWVPKLAFVLFGASLLSAHLQVTGFQIKPFTSLHFVSEPSDAV    50
  51  TMRGGNVLLNCSAESDRGVPVIKWKKDGLILALGMDDRKQQLPNGSLLIQ   100
 101  NILHSRHHKPDEGLYQCEASLADSGSIISRTAKVTVAGPLRFLSQTESIT   150
 151  AFMGDTVLLKCEVIGEPMPTIHWQKNQQDLNPLPGDSRVVVLPSGALQIS   200
 201  RLQPGDSGVYRCSARNPASIRTGNEAEVRILSDPGLHRQLYFLQRPSNVI   250
 251  AIEGKDAVLECCVSGYPPPSFTWLRGEEVIQLRSKKYSLLGGSNLLISNV   300
 301  TDDDSGTYTCVVTYKNENISASAELTVLVPPWFLNHPSNLYAYESMDIEF   350
 351  ECAVSGKPVPTVNWMKNGDVVIPSDYFQIVGGSNLRILGVVKSDEGFYQC   400
 401  VAENEAGNAQSSAQLIVPKPAIPSSSILPSAPRDVLPVLVSSRFVRLSWR   450
 451  PPAEAKGNIQTFTVFFSREGDNRERALNTTQPGSLQLTVGNLKPEAMYTF   500
 501  RVVAYNEWGPGESSQPIKVATQPELQVPGPVENLHAVSTSPTSILITWEP   550
 551  PAYANGPVQGYRLFCTEVSTGKEQNIEVDGLSYKLEGLKKFTEYTLRFLA   600
 601  YNRYGPGVSTDDITVVTLSDVPSAPPQNISLEVVNSRSIKVSWLPPPSGT   650
 651  QNGFITGYKIRHRKTTRRGEMETLEPNNLWYLFTGLEKGSQYSFQVSAMT   700
 701  VNGTGPPSNWYTAETPENDLDESQVPDQPSSLHVRPQTNCIIMSWTPPLN   750
 751  PNIVVRGYIIGYGVGSPYAETVRVDSKQRYYSIERLESSSHYVISLKAFN   800
 801  NAGEGVPLYESATTRSITDPTDPVDYYPLLDDFPTSGPDVSTPMLPPVGV   850
 851  QAVALTHEAVRVSWADNSVPKNQKTSDVRLYTVRWRTSFSASAKYKSEDT   900
 901  TSLSYTATGLKPNTMYEFSVMVTKNRRSSTWSMTAHATTYEAAPTSAPKD   950
 951  LTVITREGKPRAVIVSWQPPLEANGKITAYILFYTLDKNIPIDDWIMETI  1000
1001  SGDRLTHQIMDLSLDTMYYFRIQARNVKGVGPLSDPILFRTLKVEHPDKM  1050
1051  ANDQGRHGDGGYWPVDTNLIDRSTLNEPPIGQMHPPHGSVTPQKNSNLLV  1100
1101  ITVVTVGVLTVLVVVIVAVICTRRSSAQQRKKRATHSVSKRKGSQKDLRP  1150
1151  PDLWIHHEEMEMKNIEKPTGTDPAGRDSPIQSCQDLTPVSHSQSETQMGS  1200
1201  KSASHSGQDTEDAGSSMSTLERSLAARRATRAKLMIPMEAQSSNPAVVSA  1250
1251  IPVPTLESAQYPGILPSPTCGYPHPQFTLRPVPFPTLSVDRGFGAGRTQS  1300
1301  VSEGPTTQQQPMLPPAQPEHPSSEEAPSRTIPTACVRPTHPLRSFANPLL  1350
1351  PPPMSAIEPKVPYTPLLSQPGPTLPKTHVKTASLGLAGKARSPLLPVSVP  1400
1401  TAPEVSEESHKPTEDPASVYEQDDLSEQMASLEGLMKQLNAITGSAF     1447

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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