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

NucPred

Fetching Q9HG03 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MDFEQYGQSSQQPRQRRRRAGKRRLNNKTPIAARLALDPQLRGKVGILSE    50
  51  DLANDLFQQQALQDVTTSDDGVLYVAIAPHTPTYTSVEDQAWTILPVRIQ   100
 101  PTERSPVAMSHSTVLFPESADSLQPFLQALGKVDSSRNSLQAHRSVEIRI   150
 151  LDVAPIHLDTIFVTVERHLLRNHDDVQTKFGGGFTNAQGPNGLWGKTGKS   200
 201  VEAKKYSKRAAADAEQRLTAAVREALGAQRIVHTGDVLPLPLPSHPITYA   250
 251  PPPPARISFCEPVSQGLLMSTTKIVLVQARPQGIRAQQTMPSRSALLKQV   300
 301  AEDEADDTSNEQFYSAAEDKPGESGTEMEVTSAAEESETEGSAGSMSDSS   350
 351  DDSLEDMISLSAPELPQPPSGVMSSLTSATPRAGGRRSDGIHTPGSVASN   400
 401  FTSATMRPGRGGGKTFKVEGLLQQVPNEVLHPRPRDDEDVDSFVFVDIST   450
 451  LAKIGCFSGDWVRIEAAEEPQLNMFASLKFGSFNDSPEDSGDWRPVKIFG   500
 501  LSGLPSSKPRYAINHSGERRPSISQRPPTRLTPSVFVPPLLLGNIENPKY   550
 551  LRISPMTFATPNGSSKPGILQHMKNTAAKNPPLAKEVTLLKVSTPLSMDR   600
 601  VLQPALFAGLKQYFESRRRILKSGDLVGISVDEGLGRAVFSGTGSGDSAS   650
 651  QEEDITIRLGQGANATNAGTRKIGVAWFRVGQVAPTTVEELEETGEDQWG   700
 701  GVAVLDPATTRMVQAGSDVSRVPGVLGNGWEYWLGVKTIPKTVHDAPTPH   750
 751  GIVADPPQSVIPPLQQRIRDLMSAATSPRAIQLGMKPVFILLRSQQRHIG   800
 801  KATVATRACSDIGIHTFPIDAYDILTEGGANGGDVKTEAYLKARAERAFH   850
 851  CGANCTALLIRHIEVLTADRIVTAMSDILNDARVVIATTTDVETIPEGIR   900
 901  SLITHEFEMGAPEEKEREGILQNAVTERGIRLSADVDLGSIALKTAALVA   950
 951  GDLVDVVERAAGARTARLESLAEASKKISGSEVFVRDVLLAGGDGARGVT  1000
1001  KADFDAAVEAARKNFADSIGAPKIPNVGWDDVGGLTNVKDALVETIQLPL  1050
1051  ERPELFAKGMKKRSGILFYGPPGTGKTLLAKAIATEFSLNFFSVKGPELL  1100
1101  NMYIGESEANVRRVFQRARDARPCVVFFDELDSVAPKRGNQGDSGGVMDR  1150
1151  IVSQLLAELDGMNGGEENSGGVFVIGATNRPDLLDTALLRPGRFDKMLYL  1200
1201  GVSDTHRKQATILEALTRKFALHPDVSLDRVAEQLPLTYTGADLYALCSD  1250
1251  AMLKAITRKATAVDEKINALPNGPVSTAWFFDHLATKEDVNVMVTEEDFL  1300
1301  SAQGELVPSVSAKELEHFERIRQTFEAVDKSKQDPAAAAPQTIAEAMEAF  1350
1351  SLGGSAIPEEAPTINGDSLTPGGIHGRIKGLNRWPGNPVRSTSGQSTTSS  1400
1401  KGKGKSVSKKGKSRTGAESDGSVDGDDEDMADANSKEDEDEDDYVVRTDH  1450
1451  LRNPMEEVE                                           1459

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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