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

NucPred

Fetching O93794 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MSEPKTASERYQKISQLEHILKRPDTYIGSVEIQEQEQWIYDEETDCMID    50
  51  KTVNIVPGLFKIFDEILVNAADNKVRDPSMKRIDVTINPEENFIEVRNDG   100
 101  KGIPIEIHEKEKIYIPELIFGHLLTSSNYDDDEKKVTGGRNGYGAKLCNI   150
 151  FSTEFTLETADPKNGRKYVQTWENNMNVCHPPKITSYKKGPSYTKVAFKP   200
 201  DLSRFGMESLDSDILGVMRRRVYDINGSVRDVNVYLNGKPLKIRNFKNYV   250
 251  ELYLKSLEKMRKMDNGESDTTPSNIPTILYERVSDRWEIAFAVSDISFKQ   300
 301  VSFVNSIATTTGGTHVNYIADQIVRKVSDILKKKKKNIKPYQIKNNMFIF   350
 351  INCLIENPAFTSQTKEQLTTRVKDFGSRCDISSDYINKIMKTDLATKIFE   400
 401  IADENANNALKKSDGSRKSRITDYPKLEDANKAGTKDGYKCTLILTEGDS   450
 451  ALSLAVAGLAVVGRDYYGCYPLRGKMLNVREATADQILKNAEIQAIKKIM   500
 501  GLQHRKKYEDTKSLRYGHLMIMTDQDHDGSHIKGLIINFIETSFPGLLDI   550
 551  PGFLIEFITPIVKVTITKPIKKVISFFNLPDYEKWREEESHKYSWKQKYY   600
 601  KGLGTSTSPEIIEYFSNLDTHLKKFHALQGDDKDLIDLAFSKKKADDRKE   650
 651  WLRQYEPGTVLDPTLNEIPISDFINKELILFSLADNVRSIPSVLDGFKPG   700
 701  QRKVLYTCFKKNLTTEKKVANLAPAVSDYTAYHHGEQALVQTIIGMAQNF   750
 751  VGTNNIYFLKPNGAFGTRATGGKDAAAARYIYTELNKIARKVFHPADDPL   800
 801  FRYVQEDEKTVEPEWYLPVVPMVLINGAEGIGTGWSTSIPPFNPLDVVNN   850
 851  IRHLLNDEEMDDMHPWFRGWTGTMEKIESQRYRMYGRIEQVGPNTLEITE   900
 901  LPARTWTSTIKEHLLLGLGGSEKVKPWIKDMEEQHAETIKFIIKLTDEEM   950
 951  TKTRKLGFYERFKLISPISLQNMVAFDYRGKIKKYDHVHEILKDFYEVRL  1000
1001  EYYQKRKDYMTGRLQWEAEKLSFQVKFIKMIIDKSLIVTNKPKKQLISEL  1050
1051  EELGFPRINKEGKPHFGKIDEEVEAIISEDEDEDLEESEEATRKKDKDDE  1100
1101  STVNGPEELFGTYEYLLGLKIWSLTKERYEKLLKQKQEKETELENLLKLS  1150
1151  AKDLWNNDLDDFLTAYEDFQKMDLFLRNSAVPKTKGGKRKRKGGDDDDYD  1200
1201  PSGKKKPARRIKKIKKEDDFDRILIKPQAKIKAKRPVKVKVEPPSSAAST  1250
1251  PSVKEELGVSDVTSNASTPSTTIFDQKVKQENSDESGISAFSSKFNKIAS  1300
1301  AFDEDAPLDQITSEDTSVKESSAPAAKKKAPPKRKAKVVESSEDELSDAN  1350
1351  LSEQDDEEVVPVRRQRSSRQTAKKSYAEPIEISDEEDFIDDDEDEEVDSD  1400
1401  ESFNDE                                              1406

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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