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

NucPred

Fetching P27398 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MGTISSVLQWSCTKCNTINPTESLKCFNCGTVRKVFPQQQQQQHRSSSIT    50
  51  ASWTADDALEQEQAEKGQERDKEKGRAAVARSEYKHVYKSLLRGCLKRPQ   100
 101  RNSQNLPANCVDCEDTRKYIKSSIELYRHFSNPALNRRWVCHACGTDNSS   150
 151  VTWHCLICDTVSYLAPIYKDAIAADRGQDLAGSLGNRGELLAADHSHPHH   200
 201  HHHYLHQELEEQHQHQLHSQHLHKRHLKGRSASGSGSGPGSGSGLRRTQS   250
 251  LSTAIDKSASGRSCHICYANNQSKDIFNLPQIKPAPQLTGIPPVAACSNS   300
 301  RFAIANDTFCRRKQNNNNKNQNHKVVRESGAKRKYNFTITTLSRSAAKDA   350
 351  GHGQMKPLRQVVNLNLNLQQEPQQKSPANPQQLQRKTQREPAAVSMNPTQ   400
 401  FTIPRNGVFIAVNEWSEPMASSSSVSSSSNHHHHHHSNSNSNSSGNSNII   450
 451  NNNSSSSSGSNKLYENECVALAQQQLRAAAAQAAQAAATAVAIASSPSAK   500
 501  AMAEPAPTATMPIYAQVNKQHKLKKKQQIASESQTNNNTGSGEIADAVSE   550
 551  SLTAGLGTSTDGSGEASESESQVEEHSIYAKVWKGPRKATESKIMHDPGS   600
 601  SSRLSGAASAAAGTASAGAIAAAVGAAAASRHDNKTQLGNGSRSKMWICI   650
 651  KCSYAYNRLWLQTCEMCEAKAEQQQQQLQLQQQQQQQQQHHHHHLQQQQA   700
 701  EAPRDEPWTCKKCTLVNYSTAMACVVCGGSKLKSISSIEDMTLRKGEFWT   750
 751  CSHCTLKNSLHSPVCSACKSHRQPQLSMAMEAVRERPDGQSYEEQDAAAV   800
 801  GGGGGSAHQSGANEVKAPTALNLPLTSVALPMPMLQLPTSTAAGLRGSRS   850
 851  PSPRMQLLPSLQQQRNSSSSGAIPKRHSTGGSIVPRNISIAGLANYNLQQ   900
 901  GQGVGSASVVSASGAGSGAGAVGASTSTKKWQCPACTYDNCAASVVCDIC   950
 951  SSPRGLASAVLGEALGRKSVRVALTPADIRQESKLMENLRQLEETEALTK  1000
1001  WQNIIQYCRDNSELFVDDSFPPAPKSLYYNPASGAGEGNPVVQWRRPHEI  1050
1051  NCDGGAYPPWAVFRTPLPSDICQGVLGNCWLLSALAVLAEREDLVKEVLV  1100
1101  TKEICGQGAYQVRLCKDGKWTTVLVDDLLPCDKRGHLVYSQAKRKQLWVP  1150
1151  LIEKAVAKIHGCYEALVSGRAIEGLATLTGAPCESIPLQASSLPMPSEDE  1200
1201  LDKDLIWAQLLSSRCVRFLMGASCGGGNMKVDEEEYQQKGLRPRHAYSVL  1250
1251  DVKDIQGHRLLKLRNPWGHYSWRGDWSDDSSLWTDDLRDALMPHGASEGV  1300
1301  FWISFEDVLNYFDCIDICKVRSGWNEVRLQGTLQPLCSISCVLLTVLEPT  1350
1351  EAEFTLFQEGQRNSEKSQRSQLDLCVVIFRTRSPAAPEIGRLVEHSKRQV  1400
1401  RGFVGCHKMLERDIYLLVCLAFNHWHTGIEDPHQYPQCILAIHSSKRLLV  1450
1451  EQISPSPHLLADAIISLTLTKGQRHEGREGMTAYYLTKGWAGLVVMVENR  1500
1501  HENKWIHVKCDCQESYNVVSTRGELKTVDSVPPLQRQVIIVLTQLEGSGG  1550
1551  FSIAHRLTHRLANSRGLHDWGPPGATHCPPIENVHGLHAPRLIT        1594

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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