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

NucPred

Fetching Q9UHC1 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MIKCLSVEVQAKLRSGLAISSLGQCVEELALNSIDAEAKCVAVRVNMETF    50
  51  QVQVIDNGFGMGSDDVEKVGNRYFTSKCHSVQDLENPRFYGFRGEALANI   100
 101  ADMASAVEISSKKNRTMKTFVKLFQSGKALKACEADVTRASAGTTVTVYN   150
 151  LFYQLPVRRKCMDPRLEFEKVRQRIEALSLMHPSISFSLRNDVSGSMVLQ   200
 201  LPKTKDVCSRFCQIYGLGKSQKLREISFKYKEFELSGYISSEAHYNKNMQ   250
 251  FLFVNKRLVLRTKLHKLIDFLLRKESIICKPKNGPTSRQMNSSLRHRSTP   300
 301  ELYGIYVINVQCQFCEYDVCMEPAKTLIEFQNWDTLLFCIQEGVKMFLKQ   350
 351  EKLFVELSGEDIKEFSEDNGFSLFDATLQKRVTSDERSNFQEACNNILDS   400
 401  YEMFNLQSKAVKRKTTAENVNTQSSRDSEATRKNTNDAFLYIYESGGPGH   450
 451  SKMTEPSLQNKDSSCSESKMLEQETIVASEAGENEKHKKSFLEHSSLENP   500
 501  CGTSLEMFLSPFQTPCHFEESGQDLEIWKESTTVNGMAANILKNNRIQNQ   550
 551  PKRFKDATEVGCQPLPFATTLWGVHSAQTEKEKKKESSNCGRRNVFSYGR   600
 601  VKLCSTGFITHVVQNEKTKSTETEHSFKNYVRPGPTRAQETFGNRTRHSV   650
 651  ETPDIKDLASTLSKESGQLPNKKNCRTNISYGLENEPTATYTMFSAFQEG   700
 701  SKKSQTDCILSDTSPSFPWYRHVSNDSRKTDKLIGFSKPIVRKKLSLSSQ   750
 751  LGSLEKFKRQYGKVENPLDTEVEESNGVTTNLSLQVEPDILLKDKNRLEN   800
 801  SDVCKITTMEHSDSDSSCQPASHILNSEKFPFSKDEDCLEQQMPSLRESP   850
 851  MTLKELSLFNRKPLDLEKSSESLASKLSRLKGSERETQTMGMMSRFNELP   900
 901  NSDSSRKDSKLCSVLTQDFCMLFNNKHEKTENGVIPTSDSATQDNSFNKN   950
 951  SKTHSNSNTTENCVISETPLVLPYNNSKVTGKDSDVLIRASEQQIGSLDS  1000
1001  PSGMLMNPVEDATGDQNGICFQSEESKARACSETEESNTCCSDWQRHFDV  1050
1051  ALGRMVYVNKMTGLSTFIAPTEDIQAACTKDLTTVAVDVVLENGSQYRCQ  1100
1101  PFRSDLVLPFLPRARAERTVMRQDNRDTVDDTVSSESLQSLFSEWDNPVF  1150
1151  ARYPEVAVDVSSGQAESLAVKIHNILYPYRFTKGMIHSMQVLQQVDNKFI  1200
1201  ACLMSTKTEENGEAGGNLLVLVDQHAAHERIRLEQLIIDSYEKQQAQGSG  1250
1251  RKKLLSSTLIPPLEITVTEEQRRLLWCYHKNLEDLGLEFVFPDTSDSLVL  1300
1301  VGKVPLCFVEREANELRRGRSTVTKSIVEEFIREQLELLQTTGGIQGTLP  1350
1351  LTVQKVLASQACHGAIKFNDGLSLQESCRLIEALSSCQLPFQCAHGRPSM  1400
1401  LPLADIDHLEQEKQIKPNLTKLRKMAQAWRLFGKAECDTRQSLQQSMPPC  1450
1451  EPP                                                 1453

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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