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

NucPred

Fetching P01031 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MGLLGILCFLIFLGKTWGQEQTYVISAPKIFRVGASENIVIQVYGYTEAF    50
  51  DATISIKSYPDKKFSYSSGHVHLSSENKFQNSAILTIQPKQLPGGQNPVS   100
 101  YVYLEVVSKHFSKSKRMPITYDNGFLFIHTDKPVYTPDQSVKVRVYSLND   150
 151  DLKPAKRETVLTFIDPEGSEVDMVEEIDHIGIISFPDFKIPSNPRYGMWT   200
 201  IKAKYKEDFSTTGTAYFEVKEYVLPHFSVSIEPEYNFIGYKNFKNFEITI   250
 251  KARYFYNKVVTEADVYITFGIREDLKDDQKEMMQTAMQNTMLINGIAQVT   300
 301  FDSETAVKELSYYSLEDLNNKYLYIAVTVIESTGGFSEEAEIPGIKYVLS   350
 351  PYKLNLVATPLFLKPGIPYPIKVQVKDSLDQLVGGVPVTLNAQTIDVNQE   400
 401  TSDLDPSKSVTRVDDGVASFVLNLPSGVTVLEFNVKTDAPDLPEENQARE   450
 451  GYRAIAYSSLSQSYLYIDWTDNHKALLVGEHLNIIVTPKSPYIDKITHYN   500
 501  YLILSKGKIIHFGTREKFSDASYQSINIPVTQNMVPSSRLLVYYIVTGEQ   550
 551  TAELVSDSVWLNIEEKCGNQLQVHLSPDADAYSPGQTVSLNMATGMDSWV   600
 601  ALAAVDSAVYGVQRGAKKPLERVFQFLEKSDLGCGAGGGLNNANVFHLAG   650
 651  LTFLTNANADDSQENDEPCKEILRPRRTLQKKIEEIAAKYKHSVVKKCCY   700
 701  DGACVNNDETCEQRAARISLGPRCIKAFTECCVVASQLRANISHKDMQLG   750
 751  RLHMKTLLPVSKPEIRSYFPESWLWEVHLVPRRKQLQFALPDSLTTWEIQ   800
 801  GVGISNTGICVADTVKAKVFKDVFLEMNIPYSVVRGEQIQLKGTVYNYRT   850
 851  SGMQFCVKMSAVEGICTSESPVIDHQGTKSSKCVRQKVEGSSSHLVTFTV   900
 901  LPLEIGLHNINFSLETWFGKEILVKTLRVVPEGVKRESYSGVTLDPRGIY   950
 951  GTISRRKEFPYRIPLDLVPKTEIKRILSVKGLLVGEILSAVLSQEGINIL  1000
1001  THLPKGSAEAELMSVVPVFYVFHYLETGNHWNIFHSDPLIEKQKLKKKLK  1050
1051  EGMLSIMSYRNADYSYSVWKGGSASTWLTAFALRVLGQVNKYVEQNQNSI  1100
1101  CNSLLWLVENYQLDNGSFKENSQYQPIKLQGTLPVEARENSLYLTAFTVI  1150
1151  GIRKAFDICPLVKIDTALIKADNFLLENTLPAQSTFTLAISAYALSLGDK  1200
1201  THPQFRSIVSALKREALVKGNPPIYRFWKDNLQHKDSSVPNTGTARMVET  1250
1251  TAYALLTSLNLKDINYVNPVIKWLSEEQRYGGGFYSTQDTINAIEGLTEY  1300
1301  SLLVKQLRLSMDIDVSYKHKGALHNYKMTDKNFLGRPVEVLLNDDLIVST  1350
1351  GFGSGLATVHVTTVVHKTSTSEEVCSFYLKIDTQDIEASHYRGYGNSDYK  1400
1401  RIVACASYKPSREESSSGSSHAVMDISLPTGISANEEDLKALVEGVDQLF  1450
1451  TDYQIKDGHVILQLNSIPSSDFLCVRFRIFELFEVGFLSPATFTVYEYHR  1500
1501  PDKQCTMFYSTSNIKIQKVCEGAACKCVEADCGQMQEELDLTISAETRKQ  1550
1551  TACKPEIAYAYKVSITSITVENVFVKYKATLLDIYKTGEAVAEKDSEITF  1600
1601  IKKVTCTNAELVKGRQYLIMGKEALQIKYNFSFRYIYPLDSLTWIEYWPR  1650
1651  DTTCSSCQAFLANLDEFAEDIFLNGC                          1676

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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