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

NucPred

Fetching P49790 from www.uniprot.org...

The NucPred score for your sequence is 0.68 (see score help below)

   1  MASGAGGVGGGGGGKIRTRRCHQGPIKPYQQGRQQHQGILSRVTESVKNI    50
  51  VPGWLQRYFNKNEDVCSCSTDTSEVPRWPENKEDHLVYADEESSNITDGR   100
 101  ITPEPAVSNTEEPSTTSTASNYPDVLTRPSLHRSHLNFSMLESPALHCQP   150
 151  STSSAFPIGSSGFSLVKEIKDSTSQHDDDNISTTSGFSSRASDKDITVSK   200
 201  NTSLPPLWSPEAERSHSLSQHTATSSKKPAFNLSAFGTLSPSLGNSSILK   250
 251  TSQLGDSPFYPGKTTYGGAAAAVRQSKLRNTPYQAPVRRQMKAKQLSAQS   300
 301  YGVTSSTARRILQSLEKMSSPLADAKRIPSIVSSPLNSPLDRSGIDITDF   350
 351  QAKREKVDSQYPPVQRLMTPKPVSIATNRSVYFKPSLTPSGEFRKTNQRI   400
 401  DNKCSTGYEKNMTPGQNREQRESGFSYPNFSLPAANGLSSGVGGGGGKMR   450
 451  RERTRFVASKPLEEEEMEVPVLPKISLPITSSSLPTFNFSSPEITTSSPS   500
 501  PINSSQALTNKVQMTSPSSTGSPMFKFSSPIVKSTEANVLPPSSIGFTFS   550
 551  VPVAKTAELSGSSSTLEPIISSSAHHVTTVNSTNCKKTPPEDCEGPFRPA   600
 601  EILKEGSVLDILKSPGFASPKIDSVAAQPTATSPVVYTRPAISSFSSSGI   650
 651  GFGESLKAGSSWQCDTCLLQNKVTDNKCIACQAAKLSPRDTAKQTGIETP   700
 701  NKSGKTTLSASGTGFGDKFKPVIGTWDCDTCLVQNKPEAIKCVACETPKP   750
 751  GTCVKRALTLTVVSESAETMTASSSSCTVTTGTLGFGDKFKRPIGSWECS   800
 801  VCCVSNNAEDNKCVSCMSEKPGSSVPASSSSTVPVSLPSGGSLGLEKFKK   850
 851  PEGSWDCELCLVQNKADSTKCLACESAKPGTKSGFKGFDTSSSSSNSAAS   900
 901  SSFKFGVSSSSSGPSQTLTSTGNFKFGDQGGFKIGVSSDSGSINPMSEGF   950
 951  KFSKPIGDFKFGVSSESKPEEVKKDSKNDNFKFGLSSGLSNPVSLTPFQF  1000
1001  GVSNLGQEEKKEELPKSSSAGFSFGTGVINSTPAPANTIVTSENKSSFNL  1050
1051  GTIETKSASVAPFTCKTSEAKKEEMPATKGGFSFGNVEPASLPSASVFVL  1100
1101  GRTEEKQQEPVTSTSLVFGKKADNEEPKCQPVFSFGNSEQTKDENSSKST  1150
1151  FSFSMTKPSEKESEQPAKATFAFGAQTSTTADQGAAKPVFSFLNNSSSSS  1200
1201  STPATSAGGGIFGSSTSSSNPPVATFVFGQSSNPVSSSAFGNTAESSTSQ  1250
1251  SLLFSQDSKLATTSSTGTAVTPFVFGPGASSNNTTTSGFGFGATTTSSSA  1300
1301  GSSFVFGTGPSAPSASPAFGANQTPTFGQSQGASQPNPPGFGSISSSTAL  1350
1351  FPTGSQPAPPTFGTVSSSSQPPVFGQQPSQSAFGSGTTPNSSSAFQFGSS  1400
1401  TTNFNFTNNSPSGVFTFGANSSTPAASAQPSGSGGFPFNQSPAAFTVGSN  1450
1451  GKNVFSSSGTSFSGRKIKTAVRRRK                           1475

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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