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

NucPred

Fetching P81122 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MASAPLPGPPASAGGDGPNLNNNNNNNNHSVRKCGYLRKQKHGHKRFFVL    50
  51  RGPGTGGDEASAAGGSPPQPPRLEYYESEKKWRSKAGAPKRVIALDCCLN   100
 101  INKRADAKHKYLIALYTKDEYFAVAAENEQEQEGWYRALTDLVSEGRSGE   150
 151  GGSGTTGGSCSASLPGVLGGSAGAAGCDDNYGLVTPATAVYREVWQVNLK   200
 201  PKGLGQSKNLTGVYRLCLSARTIGFVKLNCEQPSVTLQLMNIRRCGHSDS   250
 251  FFFIEVGRSAVTGPGELWMQADDSVVAQNIHETILEAMKALKELFEFRPR   300
 301  SKSQSSGSSATHPISVPGARRHHHLVNLPPSQTGLVRRSRTDSLAATPPA   350
 351  AKCTSCRVRTASEGDGGAAGGAGTAGGRPMSVAGSPLSPGPVRAPLSRSH   400
 401  TLSAGCGGRPSKVTLAPAGGALQHSRSMSMPVAHSPPAATSPGSLSSSSG   450
 451  HGSGSYPLPPGSHPHLPHPLHHPQGQRPSSGSASASGSPSDPGFMSLDEY   500
 501  GSSPGDLRAFSSHRSNTPESIAETPPARDGSGGELYGYMSMDRPLSHCGR   550
 551  PYRRVSGDGAQDLDRGLRKRTYSLTTPARQRQVPQPSSASLDEYTLMRAT   600
 601  FSGSSGRLCPSFPASSPKVAYNPYPEDYGDIEIGSHKSSSSNLGADDGYM   650
 651  PMTPGAALRSGGPNSCKSDDYMPMSPTSVSAPKQILQPRLAAALPPSGAA   700
 701  VPAPPSGVGRTFPVNGGGYKASSPAESSPEDSGYMRMWCGSKLSMENPDP   750
 751  KLLPNGDYLNMSPSEAGTAGTPPDFSAALRGGSEGLKGIPGHCYSSLPRS   800
 801  YKAPCSCSGDNDQYVLMSSPVGRILEEERLEPQATPGAGTFGAAGGSHTQ   850
 851  PHHSAVPSSMRPSAIGGRPEGFLGQRCRAVRPTRLSLEGLQTLPSMQEYP   900
 901  LPTEPKSPGEYINIDFGEAGTRLSPPAPPLLASAASSSSLLSASSPASSL   950
 951  GSGTPGTSSDSRQRSPLSDYMNLDFSSPKSPKPSTRSGDTVGSMDGLLSP  1000
1001  EASSPYPPLPPRPSTSPSSLQQPLPPAPGDLYRLPPASAATSQGPTAGSS  1050
1051  MSSEPGDNGDYTEMAFGVAATPPQPIVAPPKPEGARVASPTSGLKRLSLM  1100
1101  DQVSGVEAFLQVSQPPDPHRGAKVIRADPQGGRRRHSSETFSSTTTVTPV  1150
1151  SPSFAHNSKRHNSASVENVSLRKSSEGSSTLGGGDEPPTSPGQAQPLVAV  1200
1201  PPVPQARPWNPGQPGALIGCPGGSSSPMRRETSVGFQNGLNYIAIDVRGE  1250
1251  QGSLAQSQPQPGDKNSWSRTRSLGGLLGTVGGSGASGVCGGPGTGALPSA  1300
1301  STYASIDFLSHHLKEATVVKE                               1321

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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