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

NucPred

Fetching P34703 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MDFIDNQAEESDASSGHSDDEEPQSKKMKMAKEKSKRKKKMVASSDEDED    50
  51  DDDDEEENRKEMQGFIADDDDEEEDAKSEKSEKSRHSGEDELDDEDLDLI   100
 101  NENYDIRETKKQNRVQLGDSSDEDEPIRRPNHEDDDLLSERGSDDGDRRK   150
 151  DRGRGDRGGYGSESERSEDDFIEDDGDAPRRHRKRHRGDENLPEGAEDDA   200
 201  RDVFGVEDFNLDEFYDDDDGEDGLEDEEEEIIEDDGEGGEIKIRRKKDTT   250
 251  KKSTLLESIEPSEIDRGFLLPGDKKIAKEDLPERFQLRRTPVTEADDDEL   300
 301  ESEALWIIKYAFEEGTVTNQADLDQDDKLDCIMNLDPSVYEDRKKAVIKS   350
 351  IKKVLQFIRVRSNSFEPTFIGFYRKEDIDNLLTMNNLWRVYDFDEKWCHL   400
 401  SEKKNKIYDLMRRMREYQELSDDLTAKRRPISDADLMDTKYAETLEQLTD   450
 451  IHANFQLLYGALLDDMIRWEKGRLTGEEEEQEYRVKFKSSIRNDKYQMCV   500
 501  ENGIGELAGRFGLTAKQFSENLNWKKHDIEQDPMLPLEAAEEYVCPAFSD   550
 551  SDMVLNGAKFMLAKEISRQPQVRHSVRQEFRQSAHFWIKPTKKGRDTIDQ   600
 601  THPLYDKRYIKSKPVRSLTAEEFLFYHKAKEDGLVDVLIMYESEEDQDSN   650
 651  NYLVNKYLSDSIFQKDEYTENVEQWNSVRDECVNMAITEMLVPYMRDELY   700
 701  NTILEEAKTAVAKKCRKEFASRISRSGYLPDFDNNDDDDDGMDQHGARRI   750
 751  MAVCYPTERDEASFGVMVDENGAIVDYLRMVHFTKRTFGGGNNGLRKAES   800
 801  MDLFKKFVQRRKPHAIGLNIEDMECTRLKRDLEEAVADLFSQNLIYKPIP   850
 851  VFLMDNEAAKVYMRSNVSLAENPDHPPTLRQALSLARLLLDPIPEYAHLW   900
 901  NIDEDIFCLSLHPLQRDIDQEQLALVLSHELVNKVNEEGVDINKCAEFPH   950
 951  YTNMLQFTCGLGPRKATDLLKSIKANDNLIESRSKLVVGCKLGPKVFMNC  1000
1001  AGFIKIDTIKVSEKTDAYVEVLDGSRVHPETYEWARKMAVDALEVDDSAD  1050
1051  PTAALQEIMESPDRLRDLDLDAFADELSRQGFGEKKSTLYDISSELSARY  1100
1101  KDLRQPFQEPTGELLYDLLARSGKEIREGAKVLGTVQSVQYRKVDKDAAD  1150
1151  SMLPDVGEDGLFTCPCCKSFTSSAPGGIQEHMLGDSRQGGCPGTPVGIRV  1200
1201  RFDNGMTGFCPNKNISSSHVDNPLTRVKINQPYYFKVLKLDKERFSLFLS  1250
1251  CKSSDLKEDDLSQRDQYWDEHQYQADLELMKSESKKKTEANTRVKRVIAH  1300
1301  PNFHNVSYEAATKMLDEMDWSECIIRPSANKDSGLSVTWKICDRVYHNFF  1350
1351  VKESAKDQVFSIGRQLSVGGEDFEDLDELIARFVQPMIQISHEITTHKYF  1400
1401  FPNGTCEETEAVEQFVREKKRELGRSPYVFSASYRQPCQFCISYMFDNTE  1450
1451  RIRHEYFKIVPHGVRFRHQNFDTLDRMMAWFKRHFHEPPIELRRSAIPAP  1500
1501  QYRVGAPPAAPYYPPQFVGYH                               1521

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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