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

NucPred

Fetching Q9CU65 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MDTSSVGTLELTDQTPVLLGSTAMATSLTNVGNSFSGPPNPLVSRSSKFQ    50
  51  NSSVEDDDDVVFIEPVQPPPSSAPLVADQRPITFTSSKNEELQGNDPKIL   100
 101  PSSKELAPQKGSVSETIVIDDEEDMETNQGQEKSSSNFIERRPSETKNRT   150
 151  NDVDFSSSTFSRSKVNAGVSNSGITTEPDSEIQIANVTTLETGVSSVSDG   200
 201  QLESTDGRDMNLMITHVTSLHNTSLGDGSNGLQSSNFGVNIQTYTPSLTS   250
 251  QTKAGVGPFNPGRMNVAGDVFQNGESAPHHNPDSWISQSASFPRNQKQQG   300
 301  VDSLSPVASLPKQIFQPSNQQPTKPVKVTCANCKKPLQKGQTAYQRKGSA   350
 351  HLFCSTTCLSSFSHKPAPKKLCVMCKKDITTMKGTIVAQVDSSESFQEFC   400
 401  STSCLSLYEDKQSPAKGALNKSRCTICGKLTEIRHEVSFKNMTHKLCSDH   450
 451  CFNRYRMANGLIMNCCEQCGEYLPSKGAGNNVLVVDGQQKRFCCQSCVTE   500
 501  YKQVGSHPSFLKEVRDHMQDSFLMQPEKYGKLTTCTGCRTQCRFFDMTQC   550
 551  IGPNGYMEPYCSTACMNSHKTKYAKSQSLGIICHFCKRNSLPQYQATMPD   600
 601  GKLYNFCNSSCVAKFQALSMQSSPNGQFVAPSDIQLKCNYCKNSFCSKPE   650
 651  ILEWENKVHQFCSKTCSDDYKKLHCIVTYCEYCQEEKTLHETVNFSGVKR   700
 701  PFCSEGCKLLYKQDFARRLGLRCVTCNYCSQLCKKGATKELDGVVRDFCS   750
 751  EDCCKKFQEWYYKAARCDCCKSQGTLKERVQWRGEMKHFCDQHCLLRFYC   800
 801  QQNEPNMTTQKGPENLHYDQGCQTSRTKMTGSAPPPSPTPNKEMKNKAIL   850
 851  CKPLTMTKATYCKPHMQTKSCQTDENWKTEYVPVPIPVPVYVPVPMHMYS   900
 901  QNIPVPTTVPVPVPVPVFLPAPLDSSEKIPATVEDLKSKVSSDPLDSELL   950
 951  TMTDMMTEEEGKAEASNINSVIIETDIIGSDLTKNSDPDIQSNMPDVPYE  1000
1001  PDLDIEIDFPRAAEELDMENEFLLPPVFGEEYEEQPRPRSKKKGTKRKAV  1050
1051  SGYQSHDDSSDNSECSFPFKYTYGVNAWKHWVKTRQLDEDLLVLDELKSS  1100
1101  KSVKLKEDLLSHTTAELNYGLAHFVNEIRRPNGENYAPDSIYYLCLGIQE  1150
1151  YLCGSNRKDNIFIDPGYQMFEQELNKILRSWQPSILPDGSIFSRVEEDYL  1200
1201  WRIKQLGSHSPVALLNTLFYFNTKYFGLKTVEQHLRLSFGTVFRHWKKNP  1250
1251  LTMENKACLRYQVSSLCGTDNEDKIATGKRKHEDDEPVFEQVENTANPSR  1300
1301  CPVKMFECYLSKSPQNLNQRMDVFYLQPECSSSTDSPVWYTSTSLDRNTL  1350
1351  ENMLVRVLLVKDIYDKDNYELDEDTD                          1376

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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