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

NucPred

Fetching O35099 from www.uniprot.org...

The NucPred score for your sequence is 0.50 (see score help below)

   1  MGTEAGEGITFSVPPFASVGFCTIPEGGSCRRGGGAATAAEGEPSLQPLL    50
  51  VPPPPPPPGSFWNVESAAAPGTSCPTTAPGSSATRGRGNSGSGGGRRTTV   100
 101  AYVINEASQGQLVVAESEALQSLREACEAVGATLETLHFGKLDFGETAVL   150
 151  DRFYNADIAVVEMSDAFRQPSLFYHLGVRESFSMANNIILYCDTNSDSLQ   200
 201  SLKEIICQKNTVCTGNYTFIPYMVTPHNKVYCCDSSFMKGLTELMQPNFE   250
 251  LLLGPICLPLVDRFVQLLKVAQASSSQYFRESILSDIRKARNLYTGKELA   300
 301  AELARIRQRVDNIEVLTADIVINLLLSYRDIQDYDSIVKLVETLEKLPTF   350
 351  DLASHHHVKFHYAFALNRRNLPGDRAKALDIMIPMVQSEEQVASDMYCLV   400
 401  GRIYKDMFLDSNFTDTESRDHGASWFKKAFESEPTLQSGINYAVLLLAAG   450
 451  HQFESSFELRKVGVKLSSLLGKKGNLEKLQSYWEVGFFLGASVLANDHLR   500
 501  VIQASEKLFRLKTPAWYLKSIVETILIYKHFVKLTTEQPSAKQELVDFWM   550
 551  DFLVEATKTDVTVVRFPVLILEPTKIYQPSYLSINNEVEEKTISIWHVLP   600
 601  DDKKGIHEWNFGASSVRGVSISKFEERCCFLYVLHNSDDFQIYFCTELHC   650
 651  KRFFEMVNTITEEKGRGAEDGDCEGDSLEYDYEYDENGDRVVLGKGTYGI   700
 701  VYAGRDLSNQVRIAIKEIPERDSRYSQPLHEEIALHKHLKHKNIVQYLGS   750
 751  FSENGFIKIFMEQVPGGSLSALLRSKWGPLKDNEQTIGFYTKQILEGLKY   800
 801  LHDNQIVHRDIKGDNVLINTYSGVLKISDFGTSKRLAGINPCTETFTGTL   850
 851  QYMAPEIIDKGPRGYGKAADIWSLGCTIIEMATGKPPFYELGEPQAAMFK   900
 901  VGMFKVHPEIPESMSAEAKAFILKCFEPDPDKRACANDLLIDEFLKVSSK   950
 951  KKKTQPKLSALSTGSNEYLRSISLPVPVLVEDTSSSSEYGSVSPDTELKA  1000
1001  DPFSFKARAKSCGEKDGKGIRTLFLGIPDENFEDHSAPPSPEEKDSGFFM  1050
1051  LRKDSERRATLHRILTEDQDKVVRNLMESLAQGAEEPKLKWEHITTLISS  1100
1101  LREFVRSTDRKIIATTLSKLKLELDFDSHGISQVQVVLFGFQDAVNKVLR  1150
1151  NHNIKPHWMFALDSIIRKAVQTAITILVPELRPHFSLASESDTADPEDLD  1200
1201  VEDEHEELSSNQTVRRPQAITEDAVATSGVSTLSSTVSHDSQNAHRSLNV  1250
1251  QLGRMKIETNRLLEELVRKERELQALLHQAIEEKDQEIRHLKLKSQPIDI  1300
1301  PGFPVCHLNSPGTTTEDSELPGWLRENGADEDTISRFLAEDYTLVDVLYY  1350
1351  VTRDDLKCLRLRGGMLCTLWKAIIDFRNKC                      1380

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.)

Go back to the NucPred Home Page.