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

NucPred

Fetching Q7PC83 from www.uniprot.org...

The NucPred score for your sequence is 0.49 (see score help below)

   1  MAQTGEDVDKAKSFQVEFACGNGVDDEEKLRSQWATVERLPTFKRVTTAL    50
  51  LHTGDDSSDIIDVTKLEDAERRLLIEKLVKQIEADNLRLLRKIRKRIDEV   100
 101  GIELPTVEVRFNDLSVEAECQVVHGKPIPTLWNTIKGSLSKFVCSKKETK   150
 151  IGILKGVSGIVRPGRMTLLLGPPGCGKTTLLQALSGRLSHSVKVGGKVSY   200
 201  NGCLLSEFIPEKTSSYISQNDLHIPELSVRETLDFSACCQGIGSRMEIMK   250
 251  EISRREKLKEIVPDPDIDAYMKAISVEGLKNSMQTDYILKILGLDICADT   300
 301  RAGDATRPGISGGQKRRLTTGEIVVGPATTLLMDEISNGLDSSTTFQIVS   350
 351  CLQQLAHIAGATILISLLQPAPETFELFDDVILLGEGKIIYHAPRADICK   400
 401  FFEGCGFKCPERKGVADFLQEVMSRKDQEQYWCHRSKPYSYISVDSFIKK   450
 451  FNESNLGFLLKEELSKPFDKSQTRKDSLCFRKYSLSKWEMLKACSRREIL   500
 501  LMKRNSFIYLFKSGLLVFNALVTMTVFLQAGATRDARHGNYLMGSMFTAL   550
 551  FRLLADGLPELTLTISRLGVFCKQKDLYFYPAWAYAIPSIILRIPLSVLD   600
 601  SFIWTVLTYYVIGYSPEVGRFFRHFIILLTFHLSCISMFRAIASICRTFV   650
 651  ACSITGAISVLLLALFGGFVIPKSSMPTWLGWGFWLSPLSYAEIGLTANE   700
 701  FFSPRWRKLTSGNITAGEQVLDVRGLNFGRHSYWTAFGALVGFVLFFNAL   750
 751  YTLALTYRNNPQRSRAIVSHGKNSQCSEEDFKPCPEITSRAKTGKVILPF   800
 801  KPLTVTFQNVQYYIETPQGKTRQLLFDITGALKPGVLTSLMGVSGAGKTT   850
 851  LLDVLSGRKTRGIIKGEIRVGGYPKVQETFARVSGYCEQFDIHSPNITVE   900
 901  ESLKYSAWLRLPYNIDAKTKNELVKEVLETVELEDIKDSMVGLPGISGLS   950
 951  TEQRKRLTIAVELVSNPSIIFLDEPTTGLDARAAAIVMRAVKNVAETGRT  1000
1001  VVCTIHQPSIDIFETFDELILMKDGGQLVYYGPLGKHSSKVIKYFESIPG  1050
1051  VPKVQKNCNPATWMLDITCKSAEHRLGMDFAQAYKDSTLYKENKMVVEQL  1100
1101  SSASLGSEALSFPSRYSQTGWGQLKACLWKQHCSYWRNPSHNLTRIVFIL  1150
1151  LNSLLCSLLFWQKAKDINNQQDLFSIFGSMYTIVIFSGINNCATVMNFIA  1200
1201  TERNVFYRERFARMYSSWAYSFSQVLVEVPYSLLQSLLCTIIVYPMIGYH  1250
1251  MSVYKMFWSLYSIFCSLLIFNYCGMLMVALTPNIHMALTLRSTFFSMVNL  1300
1301  FAGFVMPKQKIPKWWIWMYYLSPTSWVLEGLLSSQYGDVEKEITVFGEKK  1350
1351  SVSAFLEDYFGYKHDSLAVVAFVLIAFPIIVASLFAFFMSKLNFQKK     1397

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.)

Go back to the NucPred Home Page.