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

NucPred

Fetching P22023 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MRLLALVLLLLCAPLRAWTYSLRYGIPESAQVWSILVHLLGDVDNQLLTN    50
  51  LYPLVTGLDDEIDIQENLVALTSNVLRERYDKEDVADLLELYASLYPMGM   100
 101  IQHDISSNAEQDDANSSYFVLNGNRYEKPDDVFYLKSKDLTIQQKVPDVD   150
 151  VIQPYDVVIGTNSEAPILILYGCPTVIDSDFEEFNRNLFMEAMNGEGKFR   200
 201  FIWRSTCSLDGKSVEYPLTHPLEITLQNGSRMSSIPQLKKILYTVPKEIL   250
 251  VGADNDDQLHDLEPEELRELDLRVTSLISEFYQYKKDITATLNFTKSIVN   300
 301  NFPLISKQLIKVSSVNKDIITSNEELNSKGFDYNMLGLYINGQNWKITSL   350
 351  TPYNLLTALKTEYQSLLKITNLLQELEPSKCILDSKFLLNKFSQFSLGKL   400
 401  QNLQPIKMDLHTIPGFSESVIYFNDIESDPQYDELVNSVQAFFDKSKFGE   450
 451  LPEIKQNWSEIIFVIDFARLEDSEVKEALGGLVRAVNVVSQGYPQRVGLL   500
 501  PFSSDSDKSVVNKIYELKNSTDNLTELKSFLETMLLADGLSANAKHSKHI   550
 551  PVPDVFHLLDELQIDETSIIINGEIYPFRKNAWNYLIAKVIKKDTEFIRK   600
 601  ELSNSSPKNKQISVRDLLHYKSANLRHNKYTPNYFADSVYSSVNNTALES   650
 651  VCSERIGYYTKNEEYNLLHTITLVDDFGSIHALKRLRNLLHTSFVGVRIR   700
 701  IIHVGDISDIWYQLRGSLSQKDPIGSINTFIDALKLKKVKSHTYKKSGLN   750
 751  QLGLHKWLPDIPLFELQKGSFIALNGRFIHLDQNEVPETEHFEAIIKREA   800
 801  LRTIDSVFALDLLFPGFSQEIINPDLIEMISSILTRLFYQGTHIYNNGID   850
 851  YTTESSLPRMDLSEFFRPNNLTMFEDGKSASIDLLLILDPLEERTQMILS   900
 901  LVEQFRPLKFVNIQVILMPTLELNIVPIRRIYVDDADIVKSITSEDSRSD   950
 951  PEVDIEMDVPNSFIVDNNYRIKKLLIELHSFSSKTVLSTGNIDGMGGVCL  1000
1001  ALVDSAGNIIDKTTTMKTFGYGQFHTDKFLKGCYIKSCDSRYTVQSFSTD  1050
1051  GHPDFIPSDSLDILSYNPQKIAVKISEEPTHEEEYEEGRNNDTIINIFTI  1100
1101  LESGPDEEERYMQMILSILSKCPETQKVNFFILDQPFISDTLRKSCEYIN  1150
1151  SSDEMRGNVIFLNYEWPQWLRPQRFSSRRRDVSRFLFLDVLLPQNISKVL  1200
1201  YMSPTEVPLDPFDIFQFQGLKRAPLGLFRMSGDGYWKEGYWEKMLRENNL  1250
1251  EFYSTEPAFLVNLERFRELDAGDKYRIHYQRISTDAMSLVNIGQDLVNNL  1300
1301  QLEVPIRFLKGSYKKKLVINDECVSEWKKKINKFASSPGDEDVPGESVSS  1350
1351  KYQDSDNAAPLHDEL                                     1365

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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