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

NucPred

Fetching P16620 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MALLYRRMSMLLNIILAYIFLCAICVQGSVKQEWAEIGKNVSLECASENE    50
  51  AVAWKLGNQTINKNHTRYKIRTEPLKSNDDGSENNDSQDFIKYKNVLALL   100
 101  DVNIKDSGNYTCTAQTGQNHSTEFQVRPYLPSKVLQSTPDRIKRKIKQDV   150
 151  MLYCLIEMYPQNETTNRNLKWLKDGSQFEFLDTFSSISKLNDTHLNFTLE   200
 201  FTEVYKKENGTYKCTVFDDTGLEITSKEITLFVMEVPQVSIDFAKAVGAN   250
 251  KIYLNWTVNDGNDPIQKFFITLQEAGTPTFTYHKDFINGSHTSYILDHFK   300
 301  PNTTYFLRIVGKNSIGNGQPTQYPQGITTLSYDPIFIPKVETTGSTASTI   350
 351  TIGWNPPPPDLIDYIQYYELIVSESGEVPKVIEEAIYQQNSRNLPYMFDK   400
 401  LKTATDYEFRVRACSDLTKTCGPWSENVNGTTMDGVATKPTNLSIQCHHD   450
 451  NVTRGNSIAINWDVPKTPNGKVVSYLIHLLGNPMSTVDREMWGPKIRRID   500
 501  EPHHKTLYESVSPNTNYTVTVSAITRHKKNGEPATGSCLMPVSTPDAIGR   550
 551  TMWSKVNLDSKYVLKLYLPKISERNGPICCYRLYLVRINNDNKELPDPEK   600
 601  LNIATYQEVHSDNVTRSSAYIAEMISSKYFRPEIFLGDEKRFSENNDIIR   650
 651  DNDEICRKCLEGTPFLRKPEIIHIPPQGSLSNSDSELPILSEKDNLIKGA   700
 701  NLTEHALKILESKLRDKRNAVTSDENPILSAVNPNVPLHDSSRDVFDGEI   750
 751  DINSNYTGFLEIIVRDRNNALMAYSKYFDIITPATEAEPIQSLNNMDYYL   800
 801  SIGVKAGAVLLGVILVFIVLWVFHHKKTKNELQGEDTLTLRDSLSRALFG   850
 851  RRNHNHSHFITSGNHKGFDAGPIHRLDLENAYKNRHKDTDYGFLREYEML   900
 901  PNRFSDRTTKNSDLKENACKNRYPDIKAYDQTRVKLAVINGLQTTDYINA   950
 951  NFVIGYKERKKFICAQGPMESTIDDFWRMIWEQHLEIIVMLTNLEEYNKA  1000
1001  KCAKYWPEKVFDTKQFGDILVKFAQERKTGDYIERTLNVSKNKANVGEEE  1050
1051  DRRQITQYHYLTWKDFMAPEHPHGIIKFIRQINSVYSLQRGPILVHCSAG  1100
1101  VGRTGTLVALDSLIQQLEEEDSVSIYNTVCDLRHQRNFLVQSLKQYIFLY  1150
1151  RALLDTGTFGNTDICIDTMASAIESLKRKPNEGKCKLEVEFEKLLATADE  1200
1201  ISKSCSVGENEENNMKNRSQEIIPYDRNRVILTPLPMRENSTYINASFIE  1250
1251  GYDNSETFIIAQDPLENTIGDFWRMISEQSVTTLVMISEIGDGPRKCPRY  1300
1301  WADDEVQYDHILVKYVHSESCPYYTRREFYVTNCKIDDTLKVTQFQYNGW  1350
1351  PTVDGEVPEVCRGIIELVDQAYNHYKNNKNSGCRSPLTVHCSLGTDRSSI  1400
1401  FVAMCILVQHLRLEKCVDICATTRKLRSQRTGLINSYAQYEFLHRAIINY  1450
1451  SDLHHIAESTLD                                        1462

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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