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

NucPred

Fetching P80456 from www.uniprot.org...

The NucPred score for your sequence is 0.21 (see score help below)

   1  MEPAPELLFYVNGRKVVEKQVDPETMLLPYLRKKLRLTGTKYGCGGGGCG    50
  51  ACTVMISRYNRVTKKIRHYPVNACLTPICSLYGAAVTTVEGIGSTTTRLH   100
 101  PVQERIAKFHGTQCGFCTPGMVMSMYALLRNHPEPTLDQLADALGGNLCR   150
 151  CTGYRPIIEAYKTFCKTSDCCQNKENGFCCLDQGINGLPEVEEENQTRPN   200
 201  LFSEEEYLPLDPTQELIFPPELMTMAEKQPQRTRVFSGERMMWISPVTLK   250
 251  ALLEAKSTYPQAPVVMGNTSVGPGVKFKGIFHPVIISPDSIEELNVVSHT   300
 301  HSGLTLGAGLSLAQVKDILADVVQKVPEENAQTYRALLKHLGTLAGSQIR   350
 351  NMASLGGHIISRHLDSDLNPLLAVGNCTLNVLSKEGERQIPLDEQFLSRC   400
 401  PEADLKPQEILASVHIPYSRKWEFVLAFRQAQRKQNALAIVNSGMRVFFG   450
 451  EGDGIIRELAISYGGVGPTIICAKNSCQKLIGRSWNEEMLDTACRLILDE   500
 501  VSLPGSAPGGKVEFKRTLIISFLFKFYLEVSQILKRMAPGLSPHLADKYE   550
 551  SALQDLHARYSWSTLKDQDVDARQLSQDPIGHPVMHLSGVKHATGEAIYL   600
 601  DDMPAVDQELFMAFVTSPRAHAKIVSTDLLEALSLPGVVDIVTAEHLQDG   650
 651  NTFYTEKLLAADEVLCVGQLVCAVIAESEVQAKQAAKQVKIVYEDLEPVI   700
 701  LSIEEAIEQKSFFEPERKLEYGNVDEAFKVVDQILEGEIHMGGQEHFYME   750
 751  TQSVLVVPKGEDQEMDVYASTQFPKYIQDMVAAVLKLPVNKVMCHVKRVG   800
 801  GAFGGKVFKASIMAAIAAFAANKHGRAVRCILERGEDMLITGGRHPYLGK   850
 851  YKAGFMNDGRIVALDVEHYSNGGCSLDESLLVIEMGLLKMENAYKFPNLR   900
 901  CRGWACRTNLPSNTAFRGFGFPQAGLITECCITEVAAKCGLSPEKVRAIN   950
 951  FYKEIDQTPYKQEINAKNLTQCWNECLAKSSYFQRKVAVEKFNAENYWKQ  1000
1001  RGLAIIPFKYPRGLGSVAYGQAAALVHVYLDGSVLVTHGGIEMGQGVHTK  1050
1051  MIQVVSRELKMPMSNVHLRGTSTETVPNTNASGGSVVADLNGLAVKDACQ  1100
1101  TLLKRLEPIINKNPQGTWKEWAQAAFDKSISLSATGYFRGYDSNIDWDKG  1150
1151  EGHPFEYFVYGAACSEVEIDCLTGDHKTIRTDIVMDVGYSINPALDIGQV  1200
1201  EGAFIQGMGLYTIEELHYSPQGILYSRGPNQYKIPAICDIPAELNVTFLP  1250
1251  PSEKSNTLYSSKGLGESGVFMGCSVFFAIREAVCAARQARGLSAPWKLSS  1300
1301  PLTPEKIRMACEDKFTKMIPRDKPGSYVPWNVPV                  1334

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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