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

NucPred

Fetching Q9V8R9 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MPAEIKPSAPAEPETPTKSKPKSSSSSHGKPALARVTLLDGSLLDVSIDR    50
  51  KAIGRDVINSICAGLNLIEKDYFGLTYETPTDPRTWLDLEKPVSKFFRTD   100
 101  TWPLTFAVKFYPPEPSQLKEDITRYHLCLQVRNDILEGRLPCTFVTHALL   150
 151  GSYLVQSEMGDYDAEEMPTRAYLKDFKIAPNQTAELEDKVMDLHKTHKGQ   200
 201  SPAEAELHYLENAKKLAMYGVDLHPAKDSEGVDIMLGVCASGLLVYRDKL   250
 251  RINRFAWPKILKISYKRHHFYIKIRPGEFEQYESTIGFKLANHRAAKKLW   300
 301  KSCVEHHTFFRLMTPEPVSKSKMFPVFGSTYRYKGRTQAESTNTPVDRTP   350
 351  PKFNRTLSGARLTSRSMDALALAEKEKVARKSSTLDHRGDRNADGDAHSR   400
 401  SPIKNKKEKDADKEAKLREKKQKEKEEKERKEREKRELEEKKKAEKAAKA   450
 451  ALAAGAAAGAAVNGNDELNDSNKSDKSSGRRGVGIFSSGRKSKSGSPSKD   500
 501  GKDKSGKDKDKEVGRLGLVVTSGLGDNQQDQNLDEAARNAAKNRGSTTPG   550
 551  VTRQYEYAVDNDGNTSPTRKSYTPGGFRYDQDPNSRKSGADGQEQLSPTS   600
 601  QQKKIGLAFNYAPGNENALKETAEKLKAGQLSPRTQDKLNRGQLSPKSRA   650
 651  KLLQDPLLSPTTRAKLQGSAVDAAAVPLSDSQKRSYSPTKGPQGYSSGAP   700
 701  GSYKPISDPTADFLESQRYNKEPGYVGPSKADVAAGLAGAAGSKKPGSPT   750
 751  KTGKGAPGAAAAAAAGAAGAAAAAAKPKKRRVKIMVITSKFDPSTKRIDA   800
 801  ENGSIEHSTGILDPATGLIDTKYGVIDPKKGTLEALNTKTGKKEVFQGDV   850
 851  DGKTGNLHLVSGVADPKTGRLDDTLGQIVCITPQDNPVVELTVITSRIDP   900
 901  ATGKIDTVNGDVERSLGVLNLDTGLLDTKYGEINTRTGELKAIDPKSGKI   950
 951  VVSKNVKVDPGTGQITILGIVDPKTNKIDPNQGRLIEVGQQIDPIVEVTS  1000
1001  LAGKFDSKRNIIDPKTAQVETSGGQFDPKAGKIDTKYGQIDLVKHTITFN  1050
1051  DPKSGKTVTRDIKIEPTTGQIVLKNQVNPKNNKPDKDYARIISLRIVQQR  1100
1101  VDPATKAPITEVSASKDKDIVVDPKSNQIWVPTGATDPATKEQQYISSSV  1150
1151  DPKTGYVITIYGYLDPKTNEIKKQTKLDPNTIKIEPTSGKIYTATGEVDQ  1200
1201  ATGEPLYAATQVDPESGEVYTKLARVDPKTGKIVIVRILLISKTDERGRP  1250
1251  EEIDPSTCEIDPVSGRVLKFFNKTVYVYNMIDPVTGEIVQVDPNDPRFAG  1300
1301  ARTTVTHTMTLTGEIDPVTGRIKSEYGDIDPNTGDIDPATAVTDPVTGKL  1350
1351  ILNYAQIDPSHFGKQAQVQTTTETVPITRQQFFDGVKHISKGALRRDSEG  1400
1401  SSDDDMTAQYGADQVNEILIGSPAGQAGGKLGKPVSTPTVVKTTTKQVLT  1450
1451  KNIDGVTHNVEEEVRNLGTGEVTYSTQEHKADATPTDLSGAYVTATAVTT  1500
1501  RTATTHEDLGKNAKTEQLEEKTVATTRTHDPNKQQQRVVTQEVKTTATVT  1550
1551  SGDQYQRRDSVSSTSSGDSGTPIDGPYDGASVVRTDNQKSPLFTTSATTG  1600
1601  PHVESTRVVLGEDTPGFSGHGEIISTQTVSSKTRTVETITYKTERDGIVE  1650
1651  TRVEQKITIQSDGDPIDHDKALAEAIQEATAMNPDMTVEKIEIQQQTQ    1698

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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