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

NucPred

Fetching P18106 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MGFSSALQSRAAHEALIVRQDAELRLMETMKRSIQMKAKCDKEYAISLTA    50
  51  VAQQGLKIDRADEMQGSLISKSWRSYMDELDHQAKQFKFNAEQLEVVCDK   100
 101  LTHLSQDKRKARKAYQEEHAKIAARLNHLTDEVVRKKSEYQKHLEGYKAL   150
 151  RTRFEENYIKAPSRSGRKLDDVRDKYQKACRKLHLTHNEYVLSITEAIEV   200
 201  EKDFRNVLLPGLLEHQQSVQESFILLWRNILQEAAQYGDLTADKYKEIQK   250
 251  RIDTVIGSINPTEEYGEFTEKYKTSPTTPLLFQFDETLIQDIPGKLQSST   300
 301  LTVDNLTVDWLRNRLQELEGAVRDCQEKQMKMIEHVNGGSPVANGSIISN   350
 351  GSNTSNGIQSNKDSLCRQSKDLNALRCQEKQKQKLVDMIKCALNEVGCEE   400
 401  LPSGCDDDLTLEQNFIENGYNNEQQRSNSTSSPGLGIMNELMRRGGVLTL   450
 451  LRGRGRHFKRKSTPQPATPMTRSRQGRFNKLQPRSQSLGSLSVIRDGNGP   500
 501  SPARYEPITNHRLRQAASVHYLGEEIATSSTNPPDLTRLRRTQCSMLCLG   550
 551  EDEEPVVLASPAPLTQLTAAVLTNTNNNHIYADLELDKKKDTSPSPECKG   600
 601  EQIQPKKEQIRIEINQTAPQNSIDAHLDRIDELNRVLDDRLKRTLQPSDD   650
 651  VNAIESAEENHIQTRKLAKDPDSQTKRSSSSSSECRSSKDTSHSKKRSLS   700
 701  FSQKSISNIFSNLKEFSKSPLVRMGKNHILNEEQDAKRTQPSQHHHSSGS   750
 751  DCPTNSSSSSSNNNNNNKNTSSNSNHSASQSTIITSTITTTITTTTTTTP   800
 801  SKENSRLKFKVPKIQKKSKAIRNTFRSKLLNFQLKRSKPCKQCTKRRRIH   850
 851  PSKSVFDFAKEFEVEQPAGSAADEQFCNCPPAGQKPVKPSVQISGHKDHP   900
 901  FESSSGELDENSDRDIDNDEEEEDSASDDVLSMKDHCYCVPSLAASISLS   950
 951  TNRPLYEEEWFHGVLPREEVVRLLNNDGDFLVRETIRNEESQIVLSVCWN  1000
1001  GHKHFIVQTTGEGNFRFEGPPFASIQELIMHQYHSELPVTVKSGAILRRP  1050
1051  VCRERWELSNDDVVLLERIGRGNFGDVYKAKLKSTKLDVAVKTCRMTLPD  1100
1101  EQKRKFLQEGRILKQYDHPNIVKLIGICVQKQPIMIVMELVLGGSLLTYL  1150
1151  RKNSNGLTTRQQMGMCRDAAAGMRYLESKNCIHRDLAARNCLVDLEHSVK  1200
1201  ISDFGMSREEEEYIVSDGMKQIPVKWTAPEALNFGKYTSLCDVWSYGILM  1250
1251  WEIFSKGDTPYSGMTNSRARERIDTGYRMPTPKSTPEEMYRLMLQCWAAD  1300
1301  AESRPHFDEIYNVVDALILRLDNSH                           1325

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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