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

NucPred

Fetching Q6RHR9 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MSKVIQKKNHWTGRVHECTVKRGPQGELGVTVLGGAEHGEFPYVGAVAAA    50
  51  EAAGLPGGGEGPKLAEGELLLEVQGVRVSGLPRYDVLGVIDSCKEAVTFK   100
 101  AVRQGGRLNKDLRHFLNQRFQKGSPDHELQQTIRDNLYRHAVPCTTRSPR   150
 151  EGEVPGVDYSFLTVKEFLDLEQSGTLLEVGTYEGNYYGTPKPPSQPVSGK   200
 201  VITTDALHSLQSGSKQSTPKRTKSYNDMQNAGIVHPENEEEEDVPEMNSS   250
 251  FTADSGDQDEHTLQEATLPPVNSSILAAPITDPSQKFPQYLPLSAEDNLG   300
 301  PLPENWEMAYTENGEVYFIDHNTKTTSWLDPRCLNKQQKPLEECEDDEGV   350
 351  HTEELDSELELPAGWEKIEDPVYGVYYVDHINRKTQYENPVLEAKRKKQL   400
 401  EQQQQQQQPQPPQPEEWTEDHASVVPPVAPSHPPSNPEPARETPLQGKPF   450
 451  FTRNPSELKGKFIHTKLRKSSRGFGFTVVGGDEPDEFLQIKSLVLDGPAA   500
 501  LDGKMETGDVIVSVNDTCVLGHTHAQVVKIFQSIPIGASVDLELCRGYPL   550
 551  PFDPDDPNTSLVTSVAILDKEPIIVNGQETYDSPASHSSKTGKVSSMKDA   600
 601  RPSSPADVASNSSHGYPNDTVSLASSIATQPELITVHIVKGPMGFGFTIA   650
 651  DSPGGGGQRVKQIVDSPRCRGLKEGDLIVEVNKKNVQALTHNQVVDMLIE   700
 701  CPKGSEVTLLVQRGGLPVPKKSPKSQPLERKDSQNSSQHSVSSHRSLHTA   750
 751  SPSHGIQVLPEYLPADAPAPDQTDSSGQKKPDPFKIWAQSRSMYENRPMS   800
 801  PSPASGLSKGERDREINSTNFGECQIPDYQEQDIFLWRKETGFGFRILGG   850
 851  NEPGEPIYIGHIVPLGAADTDGRLRSGDELICVDGTPVIGKSHQLVVQLM   900
 901  QQAAKQGHVNLTVRRKVVFAVPKAENEVPSPASSHHSSNQPASLTEEKRT   950
 951  PQGSQNSLNTVSSGSGSTSGIGSGGGGGSGVVSAVLQPYDVEIRRGENEG  1000
1001  FGFVIVSSVSRPEAGTTFGRIIEGSPADRCGKLKVGDRILAVNGCSITNK  1050
1051  SHSDIVNLIKEAGNTVTLRIIPGDESSNATLLTNAEKIATITTTHAPSQQ  1100
1101  GTQETRTTTKPKQDSQFEFKGPQAAQEQDFYTVELERGAKGFGFSLRGGR  1150
1151  EYNMDLYVLRLAEDGPAERCGKMRIGDEILEINGETTKNMKHSRAIELIK  1200
1201  NGGRRVRLFLRRGDGSVPEYDPSSDRNGPSTGAQGVPEVRPGPPDHRPHP  1250
1251  ALESSYPPELHKSSQHAEKRAHAKDPKGNREHSKQPNEHHTWNGTSRKQD  1300
1301  SGACRPKDRPPDAWREAQPERTATNGSKRRSPEKRREGTRSADNTLERRE  1350
1351  KHEKRREISPERKRERSPTRRKDSSPSRRRRSLERLLDQRRSPERRRGGS  1400
1401  PERRAKSTDRRRARSPERRRERSLDKRNRDDKVGHREREEAGLKLEAGRS  1450
1451  PRNPPEQRRRPYKECSTDLSI                               1471

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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