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

NucPred

Fetching O89026 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MIAEPAHFYLFGLICLCSGSRLRQEDFPPRIVEHPSDLIVSKGEPATLNC    50
  51  KAEGRPTPTIEWYKGGERVETDKDDPRSHRMLLPSGSLFFLRIVHGRKSR   100
 101  PDEGVYICVARNYLGEAVSHNASLEVAILRDDFRQNPSDVMVAVGEPAVM   150
 151  ECQPPRGHPEPTISWKKDGSPLDDKDERITIRGGKLMITYTRKSDAGKYV   200
 201  CVGTNMVGERESEVAELTVLERPSFVKRPSNLAVTVDDSAEFKCEARGDP   250
 251  VPTVRWRKDDGELPKSRYEIRDDHTLKIRKVTAGDMGSYTCVAENMVGKA   300
 301  EASATLTVQEPPHFVVKPRDQVVALGRTVTFQCEATGNPQPAIFWRREGS   350
 351  QNLLFSYQPPQSSSRFSVSQTGDLTITNVQRSDVGYYICQTLNVAGSIIT   400
 401  KAYLEVTDVIADRPPPVIRQGPVNQTVAVDGTLILSCVATGSPAPTILWR   450
 451  KDGVLVSTQDSRIKQLESGVLQIRYAKLGDTGRYTCTASTPSGEATWSAY   500
 501  IEVQEFGVPVQPPRPTDPNLIPSAPSKPEVTDVSKNTVTLSWQPNLNSGA   550
 551  TPTSYIIEAFSHASGSSWQTAAENVKTETFAIKGLKPNAIYLFLVRAANA   600
 601  YGISDPSQISDPVKTQDVPPTSQGVDHKQVQRELGNVVLHLHNPTILSSS   650
 651  SVEVHWTVDQQSQYIQGYKILYRPSGASHGESEWLVFEVRTPTKNSVVIP   700
 701  DLRKGVNYEIKARPFFNEFQGADSEIKFAKTLEEAPSAPPRSVTVSKNDG   750
 751  NGTAILVTWQPPPEDTQNGMVQEYKVWCLGNETKYHINKTVDGSTFSVVI   800
 801  PSLVPGIRYSVEVAASTGAGPGVKSEPQFIQLDSHGNPVSPEDQVSLAQQ   850
 851  ISDVVRQPAFIAGIGAACWIILMVFSIWLYRHRKKRNGLTSTYAGIRKVP   900
 901  SFTFTPTVTYQRGGEAVSSGGRPGLLNISEPATQPWLADTWPNTGNNHND   950
 951  CSINCCTAGNGNSDSNLTTYSRPADCIANYNNQLDNKQTNLMLPESTVYG  1000
1001  DVDLSNKINEMKTFNSPNLKDGRFVNPSGQPTPYATTQLIQANLSNNMNN  1050
1051  GAGDSSEKHWKPPGQQKPEVAPIQYNIMEQNKLNKDYRANDTIPPTIPYN  1100
1101  QSYDQNTGGSYNSSDRGSSTSGSQGHKKGARTPKAPKQGGMNWADLLPPP  1150
1151  PAHPPPHSNSEEYNMSVDESYDQEMPCPVPPAPMYLQQDELQEEEDERGP  1200
1201  TPPVRGAASSPAAVSYSHQSTATLTPSPQEELQPMLQDCPEDLGHMPHPP  1250
1251  DRRRQPVSPPPPPRPISPPHTYGYISGPLVSDMDTDAPEEEEDEADMEVA  1300
1301  KMQTRRLLLRGLEQTPASSVGDLESSVTGSMINGWGSASEEDNISSGRSS  1350
1351  VSSSDGSFFTDADFAQAVAAAAEYAGLKVARRQMQDAAGRRHFHASQCPR  1400
1401  PTSPVSTDSNMSAVVIQKARPAKKQKHQPGHLRREAYADDLPPPPVPPPA  1450
1451  IKSPTVQSKAQLEVRPVMVPKLASIEARTDRSSDRKGGSYKGREALDGRQ  1500
1501  VTDLRTNPSDPREAQEQPNDGKGRGTRQPKRDLPPAKTHLGQEDILPYCR  1550
1551  PTFPTSNNPRDPSSSSSMSSRGSGSRQREQANVGRRNMAEMQVLGGFERG  1600
1601  DENNEELEETES                                        1612

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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