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

NucPred

Fetching P06274 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MAEPVNLIFYNKVMDRTAIKQLISRLIAHFGITYTTHILDQLKTLGFQQA    50
  51  TFGAISLGIDDLLTAPSKSWLIEDAEQYGNLSEKHHNYGSLHAVEKLRQL   100
 101  IETWYATSEYLKQEMNPNFRITDPLNPVHMMSFSGARGSTSQVHQLVGMR   150
 151  GLMSDPQGQIIDLPIQSNFREGLSLTEYIISCYGARKGVVDTAVRTSDAG   200
 201  YLTRRLVEVVQHIVVRKVDCGTLYGINVNNLSEKKNNFQQKLIGRVIAEN   250
 251  IYIDHRCIAPRNQDIGALLANRLITLKTKQIFLRSPLTCKSMNWICQLCY   300
 301  GWSLSHGNLIEMGEAVGIIAGQSIGEPGTQLTLRTFHTGGVFTGDIAEHV   350
 351  RTPFNGIIEFNENFVYPTRTRHGHPAWMCHTNLFLVIKSKNKVHNLTIPP   400
 401  KSLLLVQNNQYVESKQVIAEIRAKTSPFKEKVQKYIYSNLEGEMHWSTKV   450
 451  RHASEYIHSNIHLILKTCHIWILSGNFHKKNNDLSVLFYKNQDKIDFPIS   500
 501  LTKEKNEFSFVKNKTQLNLFLFHFYLYKKNKIFIKSQLTNNILNKINNSK   550
 551  NYNFILQEYNIKKKKNFYFLKNKNLTCPLFLKIKKNGVLKNNEIFAILDD   600
 601  PSYKVKNSGILKYGNIKVDLINQNTNFEDPQTKLFRPRYSIIKEGNFFFI   650
 651  PEEVYVLTQSLSSVFIKNNKFIQAGTLITSNIRSNTNGLVKIQKKGNNNY   700
 701  ELKILPGTIYYPNETYKISKQISILIPPGKKLFNEFECKNWTYLQWIMPS   750
 751  KEKPFVLIRPAVEYKISKKLNKSTLFDLLKKNKKVEIKTINYLLYEDDEQ   800
 801  IQIINEKNIQLIQTCLLVHWKKKYFFKEANVSFLKIKTKNNFKTFLQISL   850
 851  IEYSNLEKKKEKTISKNVLKKNYYDHFFSISKNELKNKKQGVIRIISNQN   900
 901  NGMQSFIILSSSDLVKTFKFKKLTKNISIKTNTNTSTAKFFEFNKNFKIL   950
 951  NKKKKLNLTKKNFSIGLLLFKKLGFLGNLHNIVTNSFSSFYLINYTKLIS  1000
1001  NKYSIITKFQHTCQNPKWYLIDESKKINKLILGKHINYNLFNWCFPLFSL  1050
1051  LKKKIDFQTIKLGQLLFENFVISKYKTSYPSGQIISININYFIIRLAKPY  1100
1101  LATGGATIHNNYGEFIKEGDTLITLIYERLKSGDIIQGLPKVEQLLEARP  1150
1151  INSVSINLENGFEDWNNDMIKFIGNLWGFFLSTKISMEQGQINLVDQIQK  1200
1201  VYQSQGVQISNKHIEIIVRQMTSKVITLEDGMTNVFLPGELIEFSRTQKM  1250
1251  NRALEEAVPYKPILLGITKASLNTQSFISEASFQETTRVLAKAALKGRID  1300
1301  WLKGLKENVILGGLVPAGTGSQEVIWQITLEKKKEIYLKKKKEFFTKKIN  1350
1351  NVFLYQDTFSIFPTTEIIHNVLKESISQNNKNNFSI                1386

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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