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

NucPred

Fetching P39770 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MKNHLSNVLCAMRSDFKDNHQETINKMIQFGTVKYGIVKQLKDRARSADK    50
  51  DIGSDQEENGGCSPLTTATTTASPSRSPEPEEEQPEEQSTSEQSIPEQST   100
 101  PDHQLENDIKSEAKSEIEPVEDNNNRVAMTKPSSEEREPNASGSMPSSPV   150
 151  AEASAEEAATERTPEKEKEKDVEVDVEKPDEAPSSAVPSTEVTLPGGAGA   200
 201  PVTLEAIQNMQMAIAQFAAKTIANGSNGADNEAAMKQLAFLQQTLFNLQQ   250
 251  QQLFQIQLIQQLQSQLALNQAKQEEDTEEDADQEQDQEQETDTYEEEERI   300
 301  ADMELRQKAEARMAEAKARQHLINAGVPLRESSGSPAESLKRRREHDHES   350
 351  QPNRRPSLDNTHKADTAQDALAKLKEMENTPLPFGSDLASSIITNHDDLP   400
 401  EPNSLDLLQKRAQEVLDSASQGILANSMADDFAFGEKSGEGKGRNEPFFK   450
 451  HRCRYCGKVFGSDSALQIHIRSHTGERPFKCNVCGSRFTTKGNLKVHFQR   500
 501  HAQKFPHVPMNATPIPEHMDKFHPPLLDQMSPTDSSPNHSPAPPPLGSAP   550
 551  ASFPPAFPGLQNLYRPPMEILKSLGAAAPHQYFPQELPTDLRKPSPQLDE   600
 601  DEPQVKNEPVEEKDQREEHEQEMAECSEPEPEPLPLEVRIKEERVEEQEQ   650
 651  VKQEDHRIEPRRTPSPSSEHRSPHHHRHSHMGYPPVVQPIQPAALMHPQS   700
 701  SPGSQSHLDHLPTPGQLPPREDFFAERFPLNFTTAKMLSPEHHSPVRSPA   750
 751  GGALPPGVPPPPHHHPHHMARSPFFNPIKHEMAALLPRPHSNDNSWENFI   800
 801  EVSNTCETMKLKELMKNKKISDPNQCVVCDRVLSCKSALQMHYRTHTGER   850
 851  PFKCRICGRAFTTKGNLKTHMAVHKIRPPMRNFHQCPVCHKKYSNALVLQ   900
 901  QHIRLHTGEPTDLTPEQIQAAEIRDPPPSMMPGHFMNPFAAAAFHFGALP   950
 951  GGPGGPPGPNHGAHNGALGSESSQGDMDDNMDCGEDYDDDVSSEHLSNSN  1000
1001  LEQEGDRSRSGDDFKSLLFEQKLRIDATGVVNTNPVRPRSSASSHGHSVG  1050
1051  STSAPTSPSVHASSQVIKRSSSPARSEASQGALDLTPRAAPTSSSSSRSP  1100
1101  LPKEKPVSPPSLPRSPSGSSHASANILTSPLPPTVGIDCLPPGLQHHLQQ  1150
1151  QHQHLMQQQAAVAAAAAAQHHHHQQMAALHQHQEQLRREAAEAQQKAAAA  1200
1201  AAAAAAAAAAQRQTPPQARDQRQEGGPGAGPPPNPLMGARPPFGMFPNLP  1250
1251  LFPPATTQNMCNAMNQIAQSVMPAAPFNPLALSGVRGSTTCGICYKTFPC  1300
1301  HSALEIHYRSHTKERPFKCSICDRGFTTKGNLKQHMLTHKIRDMEQETFR  1350
1351  NRAVKYMSEWNEDRE                                     1365

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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