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

NucPred

Fetching Q4WWH6 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MSARDFVEGEAVLDDEENENEEEQEEDYDGEVHEGAGTMNHYNDSSEEEE    50
  51  EDDDDEEAARAIREGFIVDEDEEIEERAERRREKRKRRREEREREDEHLD   100
 101  EEDLELIGELNPAFQSAAATESKFKRLKRGHKDHRQASQGIDDIFNSDED   150
 151  EEAAGDYGRPSHRRPMHDEMKDFIEEDVFTDDELEREREDLEIARPAKRG   200
 201  VTGLGATDAAGLDENALEDMRAAFGDGNEYLFALEMEEQEEEQEEDQEKH   250
 251  LDLKDVFEPSQLAERMLTEEDNQIRLLDEPERHQLARKPYRNLVLTEEQF   300
 301  REEAAWIANLMLLKKRIEPELREPFQRSVAKVLEFLVTDDWEVPFIFQHR   350
 351  KDYMIHATKVPVAGAPADGDTSQYTIKAEKLLNMTDLWDIFDHDLKFRAL   400
 401  VEKRNTIQKTYDNLQSLFNVNDSVVQDMLSTAVTMEELQDVQDYVHFQYA   450
 451  SQLRDINLMNGEANGDTHRRKATGRSFFERVRNGKAYGLVRAFGITADAF   500
 501  AQNALKEGRRQYTEDPAERPEEMADSFIDNDFSNASHVLKAAKALFAEEI   550
 551  VMSPKMRKVIRQAYYMNGAVDCFRTEKGLRRIDEQHPYYEFKYLRNQQLS   600
 601  DIARQPELYLRMLKAEEEGLVEVKVRFENFDHFRQRLYPDIESDNYSEIA   650
 651  DAWNRTRREVLDMALGKLERLINRSVKENIRQECENHVAKECREAFSQRL   700
 701  DQAPYKPKGMVLGTVPRVLAMSTGTGIVGRDPIHWAYVEEDGRVLENGKF   750
 751  VDLSIGDRDRSIPDGKDVEALIELLERRRPDVIGVSGMSPETRKLYKLLT   800
 801  ELVEKKDLRGATYTDERDEEISDPLEVVIVNDEVARLYQHSERAKKDHPS   850
 851  FGPLTHYCVALAKYLQSPLKEYASLGRDIVSIQFKRGQQLVAQELLLKQL   900
 901  ETALVDMVNLVGVDINEAVTDPATANLLPYVCGLGPRKAAHLLKIVNMNG   950
 951  GVVNNRVELLGVNAQYPAMGVKVWNNCASFLFIDFENADPDADPLDNTRV  1000
1001  HPEDYDIARKMAADALELDEEDIKAETDENGPGAIVRKLFRDEAQDRVND  1050
1051  LILEEYAEQLEKNLNQRKRATLETIRAELQQPYEELRKQFALLSTDDVFT  1100
1101  MLTGETSDTLAEGMVVPISIKRITDDHIDGKLDCGVDVLVPESELTDRYD  1150
1151  IPVRALYSLHQTLPAKVLFLNKKNFLCNVSLREEQVSRPTPRPRDHMRGE  1200
1201  WDDRQEAKDREMLQEKTQSGGRVMRVIKHPLFRPFNSTQAEEFLGSQSRG  1250
1251  DVVIRPSSKGPDHLAVTWKVADGIFQHIDVLELDKENEFSVGRTLKVGGR  1300
1301  YTYSDLDDLIFNHVKAMAKKVDEMMLHEKYQEGSKDATYSWLNTYTKANP  1350
1351  RRSAYAFCIDPKHPGYFQLCFKAGENAQLHSWPVKVIPQGYELQRNPYPD  1400
1401  MRALCNGFKLLFTNMQAGKR                                1420

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.