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

NucPred

Fetching P34709 from www.uniprot.org...

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

   1  MKLKYNKLLVSVVIVTFVTFGLLLAECFGKSIDYQEKSIFPSFVSQGFFE    50
  51  TRTNNEEYIIEKIAQTQENGVDMRSTLHFTQHGYLLNNISNLKIKFRQKT   100
 101  YTLNDVCFKPHITIFQQSSSSDQNEYPHYIQRLLLEMQRLSPCLIVTPLN   150
 151  CFYDIYRIHGEISNWNKNTDFLNRRLRNSYIEAIGENDERPYVKSNYGPS   200
 201  LIKSWADHMFDLPSKSFTNSTKDALFQKIKLWLLSIEPRQKTCAASIHSC   250
 251  DTPLDSEHYFNICTDMQSVDNFAEKKTKFKLEDVDEEFAMNLDCVDDQEQ   300
 301  FIEWMQELEIRKMYSHVTEKPDYPNVVNQTCDKIFHDLNSTGIEFFDGSR   350
 351  SFSSTKSQFDTMQTEIVLLTPEMLLSAMQHSDFVNGFESIWTIEKAEELI   400
 401  HEFRLALKEETEKFKENRMSKMIRVTSRVLDNTVTTKLQSFSEKQTIHFV   450
 451  VNVHSLIVILFTIFVWSGAPLRSAFMFFVRDALTCLLFCFVCSTDGVIVL   500
 501  DTELIKYIIVLTLANLYFTTRSSFCTERLSRCIQREKRFPINSNFASLIT   550
 551  VDTMTDSRQIQYFLSTVTKYQAAQDSYSNELFERFPKNWGCTSILIFPIV   600
 601  FVYWYFIDSNFDKICVSVLPSFCLAAGEELFAKNMFWKEREAMQAKQRLE   650
 651  NEEQAESITGSSLEKLFAGNKPVSNTDKANIVKKSSIIRNQKPCLQDLSP   700
 701  GTYDVSNFMKYPHQASRIFREKIIGLYLRILKLRTLGVILCIPAILLIVI   750
 751  SIGLLFIPVKRETLHTDSKQDDIFIEFEIFNFSTNWKIVNQNLKQFSEDI   800
 801  ESIGTLYTISNWQKSFERFEQETNKNASAEWNILFKWINDEPINSAVTLF   850
 851  SEKSSGNQTIANPFKFRLRYGFDAKNETTVIEIVQKIDELLSKCSKNLSP   900
 901  KAVGVLYEHYHRIAVVWNLFAFNQLTTAGIFIILLSIITFIFAITPTIKA   950
 951  TFLFSLLVVGTQIEVAALVHLFSLDHHQIYTNLALFAGFLAAWDPFCALL  1000
1001  RYRRRILYKSETRRTPELASKRRVLLPIVATADIAQFFVLLITAFSILAI  1050
1051  ICSIVPELNIFFVPTVILIVIQIVAVFNSIIVSIATKQMFESEVRHYLHR  1100
1101  DLRGSTTAVRVYNLVQKQRLASSLDEPQVELDEFSIKRSSPPCRYYAPPP  1150
1151  KYSCKKRSRSSDEDEDSDPNQPGPSNRRSPKTGNKRVRGNGDNTELYIPN  1200
1201  RYELIVSGKSVGGNTSAAWNGPGSTLEQNMNALEECFELGVDEYDFDEHD  1250
1251  GDEGCELVQDMLDRERNLMNKRSTAQRRESRNIEKMKKSQENLDKEKSEE  1300
1301  KISESKKNQDDSIESPNLPGTPANLPVDEPLPPVGRLYIVEHVLPEEYRR  1350
1351  DPLTEPPSMEDCIRAHSDPNLPPHPRADQYPASFTRPMVEYCEDIYWTHR  1400
1401  TGQLPPGLQVPRRPYDYYHITERTPPPEDLNWVPPAESPPIPIPQQAFDL  1450
1451  LEERRRNHREQQDEAREGDLSDPEV                           1475

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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