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

NucPred

Fetching P39806 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MRSDFKDNHQETINKMIQFGTVKYGIVKQLKDPARSAEKDIASDQEDNGA    50
  51  CSPLTTANASASAGNSPCPSRSPQQHSEDEREPEQVSEQELVPEVSAQSE   100
 101  SEIGEEIENNADETNADHNHNNNNNNKLVMTKPPVEHEVEQNANLNASMP   150
 151  NSTTPPATNAVIAGARAQQFGATPVTLEAIQNMQMAIAQFAAKTIANGAS   200
 201  GTDNEAAMKQLAFLQQTLFNLQQQQLFQLQLIQQLQSQLALNQVKQNDDE   250
 251  ADEELEPEEREDGETDTYEEEERIADMELRQKAEARMAESKARQHLINAG   300
 301  VPYANAPDPSHQPPHRCRLRRLKRKREEDASAKSSGASAKIFGEQESSQD   350
 351  ALNKLKEMENMPLPFGADLSSSIITNHDDLPEPNSLDLLQKRTQEVLDSA   400
 401  SQGILANNMADDFAFGDKSSDGKGRNEPFFKHRCRYCGKVFGSDSALQIH   450
 451  IRSHTGERPFKCNVCGSRFTTKGNLKVHFQRHAQKFPHVPMNATPIPEHM   500
 501  DKFHPPLLDQMSPDSSPTQSPAPATGLPPPSTSTLTQMQPSMSFASSPAF   550
 551  PGLPGIYRPPMELLKSLGATAGSTAGLPHPFFPQMPGLGAALKHTHDQSQ   600
 601  DMPTDLRKSSGPSSPHEEEDNIAARLPVKSELMEEEKTEHTMEAATRESA   650
 651  EMEPLPLEVRIKEERIDEDQMHLQEGMQKPEPLTAYATPHPQQCLIPTTH   700
 701  AAAKSPRSLPLQCHARLSLWCSHPTTSNHACAVLTGSQTHLDQLPTPDNV   750
 751  PPTMPQREDFFAERFPLNFTSKTDDHSPIRSPAGHAHAHIPRSPFFNPIK   800
 801  HEMAAFVPRPHSNDNSWENFIEVSNTSETMKLKELMKNKKISDPNQCVVC   850
 851  DRVLSCKSALQMHYRTHTGERPFKCRICGRAFTTKGNLKTHMAVHKIRPP   900
 901  MRNFHQCPVCHKKYSNALVLQQHIRLHTGEPTDLTPEQIQAAEIRDPPPS   950
 951  MMPGHFMNPFAAAAFHFGAMPGGGAGGPPGATGMPGGPHNGTLGSESSQG  1000
1001  DLDDNMDCGDGDDFDDISSEHLSNSNDPAATSDRRSSDDFKSLLFEQKLR  1050
1051  IDPTGVVNINSHQRPHSAASNPNSIGSASASPSAPTSPSSQPKPSCSPVR  1100
1101  SSCSPVRSVSETSQGALDLTPRALPPPLASSSSRSPYRQLLSVRRRPLAR  1150
1151  SVSSHRCVVPMVRALLSSQLPPSVGIDCLPPGLQHHLQQQHQHLMQQQXA  1200
1201  VAAAAAAQHHHHQMQQHAAALHQHQEHLRREAQEVQQKAAQEVQQKAAAA  1250
1251  AAAAAAAQRQESPQPPPRSGESSVGPPAQPNPLISARPPFGMFPNLPIFP  1300
1301  PATTQNMCNAMNQIAQSVMPAAPFNPLALSGVRGSTTCGICYKTFPCHSA  1350
1351  LEIHYRSHTKERPFKCNICDRGFTTKGNLKQHMLTHKIRDMEQETFRNRA  1400
1401  VK                                                  1402

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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