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

NucPred

Fetching Q3MNT0 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MMKKKISAKKKNQQQQQLHQPTMSEVTEEERTRYEEEEDVRDSPSDSSEE    50
  51  SEDDEEEIQKVREGFIVDDEEDEVQTKKRKSHKRKRDKERPHYDDALDDD   100
 101  DLELLLENSGLKRGSSSSGKFKRLKRKQIEDDEDEIESQDHQGEQQLRDI   150
 151  FSDDEEVEEEAAPRIMDEFDGFIEEDDFSDEDEQTRLERREQRKKKKQGP   200
 201  RIDTSNLSNVDRQSLSELFEVFGDGNEYDWALEAQELEDAGAIDKEEPAS   250
 251  LDEVFEHSELKERMLTEEDNLIRIIDVPERYQMYRSALTYIDLDDEELEL   300
 301  EKTWVANTLLKEKKAFLRDDWVEPFKQCVGQVVQFVSKENLEVPFIWNHR   350
 351  RDYLEYVDPDAPIPGSVRELMISEDDVWRIVKLDIEYHSLYEKRLNTEKI   400
 401  IDSLEIDDELVKDIKTLDSMVAIQDMHDYIQFTYSKEIRQREETQNRKHS   450
 451  KFALYERIRENVLYDAVKAYGITAKEFGENVQDQSSKGFEVPYRIHATDD   500
 501  PWESPDDMIERLIQDDEVIFRDEKTARDAVRRTFADEIFYNPKIRHEVRS   550
 551  TYKLYASISVAVTEKGRASIDAHSPFADIKYAINRSPADLIAKPDVLLRM   600
 601  LEAERLGLVVIKVETKDFANWFDCLFNCLKSDGFSDISEKWNQERQAVLR   650
 651  TAISRLCAVVALNTKEDLRRECERLIASKVRHGLLAKIEQAPFTPYGFDI   700
 701  GSKANVLALTFGKGDYDSAVVGVYIKHDGKVSRFFKSTENPSRNRETEDA   750
 751  FKGQLKQFFDEDETPDVVVVSGYNANTKRLHDVVYNFVSEYGISVKSEFD   800
 801  DGSSQLVKVIWGQDETARLYQNSERAKKEFPDKPTLVKYAISLGRYLQDP   850
 851  LLEYITLGDDILSLTFHEHQKLISNDLVKEVVESAFVDLVNAVGVDINES   900
 901  VRDSRLAQTLKYVGGLGPRKASGMLRNIAQKLGSVLTTRSQLIEYELTTR   950
 951  TIFINCSAALKISLNKSINVKDFEIEILDTTRIHPEDYQLAMKMAADALD  1000
1001  MDEESELHEKGGVIKELLENDPSKLNLLNLNDFANQIYKLTHKLKFRSLQ  1050
1051  AIRLELIQGFAEIRSPFRILTNEDAFFILTGEKPQMLKNTVIPATITKVT  1100
1101  KNHHDPYARIRGLKVVTPSLIQGTIDENAIPRDAEYVQGQVVQAVVLELY  1150
1151  TDTFAAVLSLRREDISRAMKGGVVREYGKWDYKAEDEDIKREKAKENAKL  1200
1201  AKTRNIQHPFYRNFNYKQAEEYLAPQNVGDYVIRPSSKGASYLTITWKVG  1250
1251  NNLFQHLLVEERSRGRFKEYIVDGKTYEDLDQLAFQHIQVIAKNVTDMVR  1300
1301  HPKFREGTLSVVHEWLESYTRANPKSSAYVFCYDHKSPGNFLLLFKVNVS  1350
1351  AKVVTWHVKTEVGGYELRSSVYPNMLSLCNGFKQAVKMSSQQTKSYNTGY  1400
1401  Y                                                   1401

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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