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

NucPred

Fetching Q98902 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MAHTQRQQGGSRGQWSRCLLLLLLLPLAAQPGRAAIQIPSSYYISDLKIP    50
  51  PAITTQPESVTVFSVEDLVMRCEASGNPSPTFHWTKDGEEFDPSSDPEMK   100
 101  VTEEAGSSVFYTLSNTMDTLKQYQGKYICYASNELGTAVSNAAVLMIDAP   150
 151  PVQQKEKKVTEKAEAGHSIALSCNPPQSSMQPIIHWMDNRLRHIRLSDRV   200
 201  MVGKDGNLYFANLLTEDSRNDYTCNIQYLATRTILAKEPITLTVNPSNLV   250
 251  PRNRRPQMMRPTGSHSTYHALRGQTLELECIVQGLPTPKVSWLRKDGEMS   300
 301  ESRISKDMFDRRLQFTNISESDGGEYQCTAENVQGRTFHTYTVTVEASPY   350
 351  WTNAPVSQLYAPGETVKLDCQADGIPSPTITWTVNGVPLSATSLEPRRSL   400
 401  TESGSLILKDVIFGDTAIYQCQASNKHGTILANTNVYVIELPPQILTENG   450
 451  NTYTFVEGQKALLECETFGSPKPKVTWESSSISLLLADPRVNLLTNGGLE   500
 501  IANVSHDDEGIYTCLVQGSNISVNAEVEVLNRTVILSPPQALRLQPGKTA   550
 551  IFTCLYVTDPKLSSPLLQWRKNDQKIFESHSDKKYTFDGPGLIISNVEPG   600
 601  DEGVYTCQIITKLDMVEASSTLTLCDRPDPPVHLQVTNAKHRVVTLNWTP   650
 651  GDDNNSPILEYVVEFEDQDMKENGWEELKRVAADKKHVNLPLWPYMSYRF   700
 701  RVIAINDQGKSDPSKLSDLYKTPADAPDSNPEDVRSESTDPDTLVITWEE   750
 751  MDKRNFNGPDFKYLVMWRRVVGSGPDWHEEYTIAPPFIVTDVQNFSAFEI   800
 801  KVQAVNKKGLGPEPDPIIGYSGEDVPLEAPLNLGVLLENSTTIRVTWSAV   850
 851  DKETVRGHLLGYKIYLTWGHHRNSRAQEPENIVMVQTGANEEKKSITNLR   900
 901  PYCHYDLAISAFNSKGEGPLSEKTSFMTPEGVPGPPMSMQMTSPSESEIT   950
 951  LHWTPPSKPNGILLGYSLQYRKMQSDDNPLQVVDIASPEITHLTLKGLDR  1000
1001  HSHYQFLLMARTAAGKGLSIEILGATTLEGLPPANISLSAEERSVNLSWE  1050
1051  ARKRHRTVGFQIHYFSKNGTKNGGKWKKTEMVNSSLQFFQLQGLTPGSHY  1100
1101  RLLFTYKNNTFWETEIQTKGTSVTEVQPSFATQGWFIGVVSAVVLLLLVL  1150
1151  LILCFIKRSKGGKYSVKDKEDGPMDSEARPMKDETFGEYRSLESDLEEKR  1200
1201  TASQPSLGEDSKLCSEDNLDFNGSSAVTTELNMDESLASQFSRHSEGPEP  1250
1251  FHGVPDNSPLNPAANPPATNGAPSFLN                         1277

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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