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

NucPred

Fetching Q6PL18 from www.uniprot.org...

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

   1  MVVLRSSLELHNHSAASATGSLDLSSDFLSLEHIGRRRLRSAGAAQKKPA    50
51 ATTAKAGDGSSVKEVETYHRTRALRSLRKDAQNSSDSSFEKNVEITEQLA 100
101 NGRHFTRQLARQQADKKKEEHREDKVIPVTRSLRARNIVQSTEHLHEDNG 150
151 DVEVRRSCRIRSRYSGVNQSMLFDKLITNTAEAVLQKMDDMKKMRRQRMR 200
201 ELEDLGVFNETEESNLNMYTRGKQKDIQRTDEETTDNQEGSVESSEEGED 250
251 QEHEDDGEDEDDEDDDDDDDDDDDDDDEDDEDEEDGEEENQKRYYLRQRK 300
301 ATVYYQAPLEKPRHQRKPNIFYSGPASPARPRYRLSSAGPRSPYCKRMNR 350
351 RRHAIHSSDSTSSSSSEDEQHFERRRKRSRNRAINRCLPLNFRKDELKGI 400
401 YKDRMKIGASLADVDPMQLDSSVRFDSVGGLSNHIAALKEMVVFPLLYPE 450
451 VFEKFKIQPPRGCLFYGPPGTGKTLVARALANECSQGDKRVAFFMRKGAD 500
501 CLSKWVGESERQLRLLFDQAYQMRPSIIFFDEIDGLAPVRSSRQDQIHSS 550
551 IVSTLLALMDGLDSRGEIVVIGATNRLDSIDPALRRPGRFDREFLFSLPD 600
601 KEARKEILKIHTRDWNPKPLDTFLEELAENCVGYCGADIKSICAEAALCA 650
651 LRRRYPQIYTTSEKLQLDLSSINISAKDFEVAMQKMIPASQRAVTSPGQA 700
701 LSTVVKPLLQNTVDKILEALQRVFPHAEFRTNKTLDSDISCPLLESDLAY 750
751 SDDDVPSVYENGLSQKSSHKAKDNFNFLHLNRNACYQPMSFRPRILIVGE 800
801 PGFGQGSHLAPAVIHALEKFTVYTLDIPVLFGVSTTSPEETCAQVIREAK 850
851 RTAPSIVYVPHIHVWWEIVGPTLKATFTTLLQNIPSFAPVLLLATSDKPH 900
901 SALPEEVQELFIRDYGEIFNVQLPDKEERTKFFEDLILKQAAKPPISKKK 950
951 AVLQALEVLPVAPPPEPRSLTAEEVKRLEEQEEDTFRELRIFLRNVTHRL 1000
1001 AIDKRFRVFTKPVDPDEVPDYVTVIKQPMDLSSVISKIDLHKYLTVKDYL 1050
1051 RDIDLICSNALEYNPDRDPGDRLIRHRACALRDTAYAIIKEELDEDFEQL 1100
1101 CEEIQESRKKRGCSSSKYAPSYYHVMPKQNSTLVGDKRSDPEQNEKLKTP 1150
1151 STPVACSTPAQLKRKIRKKSNWYLGTIKKRRKISQAKDDSQNAIDHKIES 1200
1201 DTEETQDTSVDHNETGNTGESSVEENEKQQNASESKLELRNNSNTCNIEN 1250
1251 ELEDSRKTTACTELRDKIACNGDASSSQIIHISDENEGKEMCVLRMTRAR 1300
1301 RSQVEQQQLITVEKALAILSQPTPSLVVDHERLKNLLKTVVKKSQNYNIF 1350
1351 QLENLYAVISQCIYRHRKDHDKTSLIQKMEQEVENFSCSR 1390

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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