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

NucPred

Fetching P34288 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MEEHHRRLHVKAERASVIGGDIVDGAFGSWALRAARSEHQLKQQSNEDLA    50
  51  QNARISALLGEMRPRMSAMPPNGHQQQYQPQLRRKANTTNIVDVSSQVPS   100
 101  ARNAIYGSWQDRHRPTRLYGSQLVSSSSTLPKYDQLYCNTASPLTGNGST   150
 151  NTIATTGIRREPPEYGNVGRSVSTWQVTNSEHRPSLQAGWLKSSRPLARG   200
 201  ALSPAAYFRDLENRHGSGASSPIVGGLSVVAVPITQRHAPTAGLAPISDD   250
 251  ISTSKVSLDTENQQLNNEDSDKISGSALSRNTPRQASFMAAMQRHPLKES   300
 301  STSIESNGGGTNTEEDQTVSATSKEDPSEDTGHDDPEETQEISETPIRRS   350
 351  RNRNASLRNRQSSRSLGGLDFEKLRMGTARVGDSNEATAENGTSSSSSRK   400
 401  NSRDDGLTSSPTTVAGPVFTTSSTSSISTSGEASSTAVAAAAAGSVAATT   450
 451  SRQTSSNSSVDSNHNEAMKMIRRARPKSYVLATSASMNEDVLSSSIIANE   500
 501  QSSSISHDTTTSGRELPSSLMGSTISMEMRSGGASSATTTTTSNSGQQTS   550
 551  RSLNAPHPPATHRLQRFIALFNSSKTSDGSGEHKKSRMKRSRTSLPASRF   600
 601  ALPGTILQRDGVARQTWVKHQEIALGKSGKRNNWEDRWAVLCRRSLYLCV   650
 651  ESPAYTTEKTIELGSHTRVDVCNAIVDIAYDWLSSSFSKQRHVVRIVTQN   700
 701  RSEHLIELNTESEMLSWISVLQSSSEDGIATGSSVDENELSTTGRHNNNA   750
 751  VSNSSALLHNSQSIASLASSSCSTATTSEFLNSQHTLQQQQQQQTNQKHQ   800
 801  QTVNELSAGIVSHLPTSKSFGGLSTTASSTTENAKNRLIMHRYIAKNSQL   850
 851  QSPTANKKMETDPSTVPSSSQTMATTSSSFHHHSSQAGPSRDIENGEAPT   900
 901  ATATTPKSGRKWKKSKAAKQGSGGGSSGSSSGSQQQGAAGAPQPVLGVRI   950
 951  ADCPTGSCEDHVPMIVQACVCVIETYGMDTVGIYRIPGNTAAVNALKESL  1000
1001  SNRGFDSVDLSKVESLDPRWRDVNVVSSLLKMFLRKLPEPLLTDKLYPFF  1050
1051  IDANRISTHHNRLHKLRNLLRKLPRPHYDTLRFLIVHLSEITKHSDVNKM  1100
1101  ECRNLALMFGPSIVRPSDDNMATMVTHMSDQCKIIETLIHYNLWMFDESS  1150
1151  TTEDAVPEQHPADGQNPLEPGGYGVGVPTGVSAASFNDMHNLIRKANEDQ  1200
1201  AAAMMNEGKGQKIKNMLRRNSRRDKSKSKLKIESTAPAAVNPRGWTQPTP  1250
1251  SNTSAASVESAFCGNYQERDIDAEIESRQTVSPQMTSGSADGASSTRLDQ  1300
1301  SPSLESSLGSLPDTSRTEPILGSSGYDDDEAKEAARRKRQEEMYSARRIF  1350
1351  IAGAAGAAAAATTTADAEKAAIDALANHSQHLHLASSPAFEVLSEETREK  1400
1401  IRRMQKKQSWHDTKELRSGELLKTYSPTKDLTDALSCTSDYSTTSSAPLS  1450
1451  TNPPLAVACADQPNSSSDYASSDPSPCARNPSTSPASRPSNLAISPAQLH  1500
1501  ATSSSGQSHQPMSRSQKIRLRTKLGSRDPARRHTLSDVDTLKEGRLDKLA  1550
1551  RWFGIRKSSPDVSRDEVSDDEKNHQEAPPLPAAAPPVIVRTSPNELTPVS  1600
1601  GDELL                                               1605

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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