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

NucPred

Fetching Q99MV7 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MAAEASSTGLASCHLVESKSGAQGASGCQCTRCGRKVSVASGDHHKFPCG    50
  51  HAFCELCLLAPQEYTTSKCTDCEVHTTVSMNQGHYPVDGFIEEDSSLEAL   100
 101  PPKMVNNCSSDLEKTVDQLINDLEHSSSIHRNVSNPSAVMSETEEIDEAL   150
 151  KIAGCNFEQLSNAIKMLDSTQDQTRQETHSLTEAVEKQFDTLLASLDSRK   200
 201  KSLCEELIRRTDDYLSKLVTVKSYIEEKKSDLDAAMKIAKELRSAPSLRT   250
 251  YCDLTQIIRTLKLTFESELSQVSSIIPRNTPRLDINCSEAICMFSSMGKI   300
 301  EFEDSTKCYPQENEDGQNVQKKFNNRKELCCDVYSSLEKKKVDAAVLTDE   350
 351  TPEPPLQAEAPDRHLEGKKKQPTKEMVVVTSPKTIAVLPQLGSSPDVIIE   400
 401  EIIEENLESCFTDDPIETSGYPKKPPQKEQSAPVGSKAGCPELVFVSHVI   450
 451  HPCHFYVRKYSQIKDATILEKKMKQVCNRSLHLDPSDILELGARIFVNSI   500
 501  KNRMWCRGIITEIIPSKTKNIRKPCSPTKFSVCEISLIQIFMVDFGNSEV   550
 551  LIITGVGDTHEGPEHDGEQHITLSDFCLLLMKSEPYSEELLKDIPHLAHL   600
 601  CSLKDIVPYNSTEGWEKEAKVEFLKMVNKKAVLMKVFGEEDDVLIVDLQK   650
 651  PPTNKISSDMPVSLRDALVFMELARFRSQSPRSHSEKNTTLCYHPPILPE   700
 701  EMTEVSVMVCHINSPTDFYLQLMENLDFLSLLKTIEEFYKGEDGENLEIL   750
 751  CPLQNQACVAKFEDGIWYRAKVIGLPGHREVEVKYVDFGNTAKITLKDMR   800
 801  KIKDEFLEPPEKAIKCKLAYVEPSKKSQWSKKAKEKFEEKTQDKFVTCSV   850
 851  IKILENNVLLVELFDSRAPGKSAVSINDQLVKEGLASYEAGYTLKDNSKK   900
 901  HLEVWDPSPEEIITSEINNLSPLSVKSLPNENFQSLYNKELPVNICNVIS   950
 951  PEKIYVQWLLTENLLNSLEEKMVAAYEHSEWKPVKWECDMHCAVKVPAKN  1000
1001  QWRRGQILRMVTDKLVEVLLYDVGVELVVNIHCLRELQENLKTMGRLSLE  1050
1051  CSLVDIRPTGGSDKWTATACDCLSLHLTGAIATIILQESNTTWPLPVKIF  1100
1101  CRDEKGERVDVSKYLIKKGLALRERRVSKSSNSHSPEKSLEIPLEQGDSV  1150
1151  VTKCFKINFDTNKKIADKVNEHKVPDSKGKKSESRSTGCYRPPAVPNTSS  1200
1201  FEAIVTCIGDDGTIFVVPKLSEFELIKMMDEIQSNLKCLGLLEPYSWKKG  1250
1251  EPCAVRGSDTLWYRGKVMEVVGGTIRVQYLDHGFTEKIPQCHLYPILLYP  1300
1301  DTPQFCIPCQLYQTLPVGNTWQPDAIELLQELLSKREVDIHIMELPNNSW  1350
1351  GKLSVHLYFDGMSLSHFMAHHKYCIFEHTEEIFKEKPRGQNKKYEDENWK  1400
1401  IRFEDLLLPEMEAPVLPPYLSSLLPPPEELFAVQVKHIVSPDEMYICLDS  1450
1451  EDSYTQFNHHGDTDDSGVSWESESENLEEALQRFNKNVETFPPLTDFSSE  1500
1501  MPCLAEYADGLWYRAKIISIKEFNPLSVLVLFVDYGCTEKLTINRLRQIP  1550
1551  VQLMQYPAQAIKVLLAGFKPPLSDSGKTRIPYCPKWSMEALWTMIDCLQG  1600
1601  KQLYASSVAQAPEQIVTLYEDEQYPVHMSLVEMGLADKDE            1640

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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