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

NucPred

Fetching Q05909 from www.uniprot.org...

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

   1  MRRLLEPCWWILFLKITSSVLHYVVCFPALTEGYVGTLQESRQDSSVQIR    50
  51  RRKASGDPYWAYSGAYGPEHWVTSSVSCGGSHQSPIDILDHHARVGDEYQ   100
 101  ELQLDGFDNESSNKTWMKNTGKTVAILLKDDYFVSGAGLPGRFKAEKVEF   150
 151  HWGHSNGSAGSEHSVNGRRFPVEMQIFFYNPDDFDSFQTAISENRIIGAM   200
 201  AIFFQVSPRDNSALDPIIHGLKGVVHHEKETFLDPFILRDLLPASLGSYY   250
 251  RYTGSLTTPPCSEIVEWIVFRRPVPISYHQLEAFYSIFTTEQQDHVKSVE   300
 301  YLRNNFRPQQALNDRVVSKSAVRDAWNHDLADFLDNPLGTEASKVCSSPP   350
 351  IHMKVQPLNQTALQVSWSQPETIYHPPIMNYMISYSWTKNEDEKEKTFTK   400
 401  DSDKDLKATISHVSPDSLYLFRVQAVCRNDMRSDFSQTMLFQANTTRIFQ   450
 451  GTRIVKTGVPTASPASSADMAPISSGSSTWTSSGIPFSFVSMATGMGPSS   500
 501  SGSQATVASVVTSTLLAGLGFGGGGISSFPSTVWPTRLPTASAASKQAGR   550
 551  TVLATTEALASPGPDVHSAPSKDSEGTEEGEKEEKSESEDGEREHEEEEK   600
 601  DSEKKEKSEATHTAAESDRTAPAPTPSSPHRTAAEGGHQTIPGRRQDHSA   650
 651  PATDQPGHVAPDLDPLVDTATQVPPTATEEHYSGSDPRRPEMPSKKPMSR   700
 701  GDRFSEDSKFITVNPAEKNTSGMLSRPSPGRMEWIIPLIVVSALTFVCLV   750
 751  LLIAVLVYWRGCNKIKSKGFPRRSREVPSSGERGEKGSRKCFQTAHFYVE   800
 801  DSSSPRVVPNESVPIIPIPDDMEAIPVKQFGKHIGELYSNSQHGFSEDFE   850
 851  EVQRCTADMNITAEHSNHPDNKHKNRYINILAYDHSRVKLRPLPGKDSKH   900
 901  SDYINANYVDGYNKAKAYIATQGPLKSTFEDFWRMIWEQNTGIIIMITNL   950
 951  VEKGRRKCDQYWPTENTEEYGNIIVTLKSTKVHACYTVRRLSVRNTKVKK  1000
1001  GQKGNPKGRQNERTVIQYHYTQWPDMGVPEYALPVLTFVRRSSAARMPDM  1050
1051  GPVLVHCSAGVGRTGTYIVIDSMLQQIKDKSTVNVLGFLKHIRTQRNYLV  1100
1101  QTEEQYIFIHDALLEAILGKETAVSSSQLHSYVNSILIPGVGGKTRLEKQ  1150
1151  FKLITQCNAKYVECFSAQKECNKEKNRNSSVVPAERARVGLAPLPGMKGT  1200
1201  DYINASYIMGYYRSNEFIITQHPLPHTTKDFWRMIWDHNAQIIVMLPDNQ  1250
1251  SLAEDEFVYWPSREESMNCEAFTVTLISKDRLCLSNEEQIIIHDFILEAT  1300
1301  QDDYVLEVRHFQCPKWPNPDAPISSTFELINVIKEEALTRDGPTIVHDEY  1350
1351  GAVSAGMLCALTTLSQQLENENAVDVFQVAKMINLMRPGVFTDIEQYQFV  1400
1401  YKAMLSLISTKENGNGPMTGDKNGAVLTAEESDPAESMESLV          1442

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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