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

NucPred

Fetching P35125 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MDMVENADSLQAQERKDILMKYDKGHRAGLPEDKGPEPVGINSSIDRFGI    50
  51  LHETELPPVTAREAKKIRREMTRTSKWMEMLGEWETYKHSSKLIDRVYKG   100
 101  IPMNIRGPVWSVLLNIQEIKLKNPGRYQIMKERGKRSSEHIHHIDLDVRT   150
 151  TLRNHVFFRDRYGAKQRELFYILLAYSEYNPEVGYCRDLSHITALFLLYL   200
 201  PEEDAFWALVQLLASERHSLPGFHSPNGGTVQGLQDQQEHVVPKSQPKTM   250
 251  WHQDKEGLCGQCASLGCLLRNLIDGISLGLTLRLWDVYLVEGEQVLMPIT   300
 301  SIALKVQQKRLMKTSRCGLWARLRNQFFDTWAMNDDTVLKHLRASTKKLT   350
 351  RKQGDLPPPAKREQGSLAPRPVPASRGGKTLCKGYRQAPPGPPAQFQRPI   400
 401  CSASPPWASRFSTPCPGGAVREDTYPVGTQGVPSLALAQGGPQGSWRFLE   450
 451  WKSMPRLPTDLDIGGPWFPHYDFEWSCWVRAISQEDQLATCWQAEHCGEV   500
 501  HNKDMSWPEEMSFTANSSKIDRQKVPTEKGATGLSNLGNTCFMNSSIQCV   550
 551  SNTQPLTQYFISGRHLYELNRTNPIGMKGHMAKCYGDLVQELWSGTQKSV   600
 601  APLKLRRTIAKYAPKFDGFQQQDSQELLAFLLDGLHEDLNRVHEKPYVEL   650
 651  KDSDGRPDWEVAAEAWDNHLRRNRSIIVDLFHGQLRSQVKCKTCGHISVR   700
 701  FDPFNFLSLPLPMDSYMDLEITVIKLDGTTPVRYGLRLNMDEKYTGLKKQ   750
 751  LRDLCGLNSEQILLAEVHDSNIKNFPQDNQKVQLSVSGFLCAFEIPVPSS   800
 801  PISASSPTQIDFSSSPSTNGMFTLTTNGDLPKPIFIPNGMPNTVVPCGTE   850
 851  KNFTNGMVNGHMPSLPDSPFTGYIIAVHRKMMRTELYFLSPQENRPSLFG   900
 901  MPLIVPCTVHTRKKDLYDAVWIQVSWLARPLPPQEASIHAQDRDNCMGYQ   950
 951  YPFTLRVVQKDGNSCAWCPQYRFCRGCKIDCGEDRAFIGNAYIAVDWHPT  1000
1001  ALHLRYQTSQERVVDKHESVEQSRRAQAEPINLDSCLRAFTSEEELGESE  1050
1051  MYYCSKCKTHCLATKKLDLWRLPPFLIIHLKRFQFVNDQWIKSQKIVRFL  1100
1101  RESFDPSAFLVPRDPALCQHKPLTPQGDELSKPRILAREVKKVDAQSSAG  1150
1151  KEDMLLSKSPSSLSANISSSPKGSPSSSRKSGTSCPSSKNSSPNSSPRTL  1200
1201  GRSKGRLRLPQIGSKNKPSSSKKNLDASKENGAGQICELADALSRGHMRG  1250
1251  GSQPELVTPQDHEVALANGFLYEHEACGNGCGDGYSNGQLGNHSEEDSTD  1300
1301  DQREDTHIKPIYNLYAISCHSGILSGGHYITYAKNPNCKWYCYNDSSCEE  1350
1351  LHPDEIDTDSAYILFYEQQGIDYAQFLPKIDGKKMADTSSTDEDSESDYE  1400
1401  KYSMLQ                                              1406

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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