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

NucPred

Fetching O70546 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MKSCGVSLATAAAAAAAAAFGDEEKKMAAGKASGESEEASPSLTAEEREA    50
  51  LGGLDSRLFGFVRFHEDGARMKALLGKAVRCYESLILKAEGKVESDFFCQ   100
 101  LGHFNLLLEDYPKALSAYQRYYSLQSDYWKNAAFLYGLGLVYFHYNAFQW   150
 151  AIKAFQEVLYVDPSFCRAKEIHLRLGLMFKVNTDYESSLKHFQLALVDCN   200
 201  PCTLSNAEIQFHIAHLYETQRKYHSAKEAYEQLLQTENLSAQVKATILQQ   250
 251  LGWMHHTVDLLGDKATKESYAIQYLQKSLEADPNSGQSWYFLGRCYSSIG   300
 301  KVQDAFISYRQSIDKSEASADTWCSIGVLYQQQNQPMDALQAYICAVQLD   350
 351  HGHAAAWMDLGTLYESCNQPQDAIKCYLNATRSKNCSNTSGLAARIKYLQ   400
 401  AQLCNLPQGSLQNKTKLLPSIEEAWSLPIPAELTSRQGAMNTAQQNTSDN   450
 451  WSGGNAPPPVEQQTHSWCLTPQKLQHLEQLRANRNNLNPAQKLMLEQLES   500
 501  QFVLMQQHQMRQTGVAQVRPTGILNGPTVDSSLPTNSVSGQQPQLPLTRM   550
 551  PSVSQPGVHTACPRQTLANGPFSAGHVPCSTSRTLGSTDTVLIGNNHVTG   600
 601  SGSNGNVPYLQRNAPTLPHNRTNLTSSTEEPWKNQLSNSTQGLHKGPSSH   650
 651  LAGPNGERPLSSTGPSQHLQAAGSGIQNQNGHPTLPSNSVTQGAALNHLS   700
 701  SHTATSGGQQGITLTKESKPSGNTLTVPETSRQTGETPNSTASVEGLPNH   750
 751  VHQVMADAVCSPSHGDSKSPGLLSSDNPQLSALLMGKANNNVGPGTCDKV   800
 801  NNIHPTVHTKTDNSVASSPSSAISTATPSPKSTEQTTTNSVTSLNSPHSG   850
 851  LHTINGEGMEESQSPIKTDLLLVSHRPSPQIIPSMSVSIYPSSAEVLKAC   900
 901  RNLGKNGLSNSSILLDKCPPPRPPSSPYPPLPKDKLNPPTPSIYLENKRD   950
 951  AFFPPLHQFCTNPNNPVTVIRGLAGALKLDLGLFSTKTLVEANNEHMVEV  1000
1001  RTQLLQPADENWDPTGTKKIWHCESNRSHTTIAKYAQYQASSFQESLREE  1050
1051  NEKRSHHKDHSDSESTSSDNSGKRRKGPFKTIKFGTNIDLSDDKKWKLQL  1100
1101  HELTKLPAFVRVVSAGNLLSHVGHTILGMNTVQLYMKVPGSRTPGHQENN  1150
1151  NFCSVNINIGPGDCEWFVVPEGYWGVLNDFCEKNNLNFLMGSWWPNLEDL  1200
1201  YEANVPVYRFIQRPGDLVWINAGTVHWVQAIGWCNNIAWNVGPLTACQYK  1250
1251  LAVERYEWNKLQNVKSIVPMVHLSWNMARNIKVSDPKLFEMIKYCLLRTL  1300
1301  KQCQTLREALIAAGKEIIWHGRTKEEPAHYCSICEVEVFDLLFVTNESNS  1350
1351  RKTYIVHCQDCARKTSGNLENFVVLEQYKMEDLMQVYDQFTLAPPLPSAS  1400
1401  S                                                   1401

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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