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

NucPred

Fetching O15320 from www.uniprot.org...

The NucPred score for your sequence is 0.72 (see score help below)

   1  MAKFGVHRILLLAISLTKCLESTKLLADLKKCGDLECEALINRVSAMRDY    50
  51  RGPDCRYLNFTKGEEISVYVKLAGEREDLWAGSKGKEFGYFPRDAVQIEE   100
 101  VFISEEIQMSTKESDFLCLLGVSYTFDNEDSELNGDYGENIYPYEEDKDE   150
 151  KSSIYESDFQIEPGFYATYESTLFEDQVPALEAPEDIGSTSESKDWEEVV   200
 201  VESMEQDRIPEVHVPPSSAVSGVKEWFGLGGEQAEEKAFESVIEPVQESS   250
 251  FRSRKIAVEDENDLEELNNGEPQTEHQQESESEIDSVPKTQSELASESEH   300
 301  IPKPQSTGWFGGGFTSYLGFGDEDTGLELIAEESNPPLQDFPNSISSDKE   350
 351  ATVPCTEILTEKKDTITNDSLSLKPSWFDFGFAILGFAYAKEDKIMLDDR   400
 401  KNEEDGGADEHEHPLTSELDPEKEQEIETIKIIETEDQIDKKPVSEKTDE   450
 451  SDTIPYLKKFLYNFDNPWNFQNIPKETELPFPKQILDQNNVIENEETGEF   500
 501  SIDNYPTDNTKVMIFKSSYSLSDMVSNIELPTRIHEEVYFEPSSSKDSDE   550
 551  NSKPSVDTEGPALVEIDRSVENTLLNSQMVSTDNSLSSQNYISQKEDASE   600
 601  FQILKYLFQIDVYDFMNSAFSPIVILTERVVAALPEGMRPDSNLYGFPWE   650
 651  LVICAAVVGFFAVLFFLWRSFRSVRSRLYVGREKKLALMLSGLIEEKSKL   700
 701  LEKFSLVQKEYEGYEVESSLKDASFEKEATEAQSLEATCEKLNRSNSELE   750
 751  DEILCLEKELKEEKSKHSEQDELMADISKRIQSLEDESKSLKSQVAEAKM   800
 801  TFKIFQMNEERLKIAIKDALNENSQLQESQKQLLQEAEVWKEQVSELNKQ   850
 851  KVTFEDSKVHAEQVLNDKESHIKTLTERLLKMKDWAAMLGEDITDDDNLE   900
 901  LEMNSESENGAYLDNPPKGALKKLIHAAKLNASLKTLEGERNQIYIQLSE   950
 951  VDKTKEELTEHIKNLQTEQASLQSENTHFENENQKLQQKLKVMTELYQEN  1000
1001  EMKLHRKLTVEENYRLEKEEKLSKVDEKISHATEELETYRKRAKDLEEEL  1050
1051  ERTIHSYQGQIISHEKKAHDNWLAARNAERNLNDLRKENAHNRQKLTETE  1100
1101  LKFELLEKDPYALDVPNTAFGREHSPYGPSPLGWPSSETRAFLSPPTLLE  1150
1151  GPLRLSPLLPGGGGRGSRGPGNPLDHQITNERGESSCDRLTDPHRAPSDT  1200
1201  GSLSPPWDQDRRMMFPPPGQSYPDSALPPQRQDRFCSNSGRLSGPAELRS  1250
1251  FNMPSLDKMDGSMPSEMESSRNDTKDDLGNLNVPDSSLPAENEATGPGFV  1300
1301  PPPLAPIRGPLFPVDARGPFLRRGPPFPPPPPGAMFGASRDYFPPGDFPG  1350
1351  PPPAPFAMRNVYPPRGFPPYLPPRPGFFPPPPHSEGRSEFPSGLIPPSNE  1400
1401  PATEHPEPQQET                                        1412

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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