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

NucPred

Fetching P53127 from www.uniprot.org...

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

   1  MPKEEDFQLPRRREAAKNVNYNEMEIDTKLVQQIQIAEKSGAKTKGSNSQ    50
  51  TPRNCKRTSNPASRNEKFKYQKFLHDKNTCWNFIPTLPPSFRKNSRFSNI   100
 101  LDLDDAMIDLKKMSLFNTESVLLSANDTIYMISEPAGEPYYVGRVVNFVS   150
 151  KPEFSNTIHEAIKTTSVFPAKFFQVRMNWFYRPRDIQEHVNTFNPRLVYA   200
 201  SLHQDICPISSYRGKCSIFHKDEVFDVLPNEKECIIRPNIFYFDELFDRY   250
 251  TLKYYKVYSTDKILNKWNSKSPFLYVLNRRFRYIYTEPKYPLENVLKKYV   300
 301  FHELEVNELSPADYQWDKRCQFCKEWCIQKESLSCDECGVCAHLYCMDPP   350
 351  LDRKPNKDVVWTCFSCLQKQQGTKDSHVRFLEEQALELDFIRSVRQKIEE   400
 401  ISSKAIKENVGYNTENCWFQYLGIYSISHIGDALNDSMFFPYPFKPSRVG   450
 451  VKYQWNGCNHNVPWRRNSYISANSEEERGSTKTSELAWVLDASKITTRKL   500
 501  SEYIEQCKSEICPILNVRGETCNFIDVVLKNLLFTNYDTAEAFKKCKREL   550
 551  SRKFLKEPSFTAVEIRKFEEAVEKFGSELRPVCEYVGTQPMSMIVRFYYN   600
 601  WKKTERGLTVRGKLSKLSKNKRKKEIANHENDVETKYIDDSSFDTEKLSL   650
 651  AESSFQCMFCKTDYSPMWYRVTGGSDDEKIKIRMQTGVNEKTEISEKSPA   700
 701  HSKKNEKLGALCIRCARMWRRYAIKWVPPLETLRKITGTCQNSFYSAIEG   750
 751  IIEENNTNKFTLSPFQAHNKLLEWELVQDSELIIRQRMKVYKNPNSFVKM   800
 801  KRYSMTFHTQLYKMAVRSYRKNEFHPETMQRDLELFIEDNKEVRKAIPEQ   850
 851  KPERAKNTKDEFPVNIIRQSPGTIKTSDTSRNRKCNDVFIEKASNNNIPK   900
 901  ITNASNDLIEISIKTGGSSSGSVSVDKGFKFVKFDNKTFQRLRNSLKLVN   950
 951  NKLPKYNEPSTKKIKMINDIALSNPLNEPNGASYNYTVISHSKETSVALE  1000
1001  KYHDGNKPSKMLEKDMILKHTKNKPKNPDTAWANNSARTFCSVCKEKFND  1050
1051  NDNYEVVCGNCGLTVHYFCYAIKLPKDMKKNTNLKTFKWLCDPCSNDLNP  1100
1101  IISTTYQCSMCPTKDYDYDRYRSQSFKICPDALKCTSLGTWVHLVCSLFN  1150
1151  EDIKYGNGQSMQPALNTTAVLIKHSRFTCGVCRINGGGLVKCNKCQYRYH  1200
1201  ITCAQNSSNFKLMFEKKNMSVDTTLPCIKDVKLNDTYTLRPILICDRHDI  1250
1251  SLEGNELYPLSYKPQHTLSYIEQYCRYYKCESDHSLVELRYFEQLRLRHG  1300
1301  EMPGNSHDSAIKPKIYVLPFERTCPHCGTNKSLYWYEDIICHSCNLRSGA  1350
1351  QELDFDSASANISNDNGLPVEITQQLMEGIEPAMFDIDISEAGTDKNTHP  1400
1401  SSQ                                                 1403

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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