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

NucPred

Fetching O19132 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MEEHVFGVQQIQPNVISVRLFKRKVGGLGFLVKERVSKPPVIISDLIRGG    50
  51  AAEQSGLIQAGDIILAVNGRPLVDLSYDSALEVLRGVASETHVVLILRGP   100
 101  EGFTTNLETTFTGDGTPKTIRVTQPLGAPTKAVDLSHQPPSAGKEQPRPV   150
 151  DGAAGPGSWPQPTQGHGQEAGSPSRANGLAPRTSSQDPAKKSGWAGLQGS   200
 201  GDKNELLKEIEPVLTLLAGGSKAVDGGGPAKAETRDTGVQVDRDFDAKSH   250
 251  KPLPLGVENDRVFSDLWGKGSAPVVLNNPYSEKEQPPASGKQSPTKNGSP   300
 301  SKCPRFLKVKNWETDVVLTDTLHLKSTLETGCTEHICMGSIMFPSQHTRR   350
 351  PEDIRTKEQLFPLAKEFIDQYYSSIKRFGSKAHMERLEEVNKEIESTSTY   400
 401  QLKDTELIYGAKHAWRNASRCVGRIQWSKLQVFDARDCTTAHGMFNYICN   450
 451  HIKYATNKGNLRSAITIFPQRTDGKHDFRVWNSQLIRYAGYKQPDGSTLG   500
 501  DPANVQFTEICIQQGWKPPRSRFDVLPLLLQANGNDPELFQIPPELVLEV   550
 551  PIRHPKFEWFKDLGLKWYGLPAVSNMLLEIGGLEFSACPFSGWYMGTEIG   600
 601  VRDYCDNSRYNILEEVAKKMNLDMRKTSSLWKDQALVEINIAVLYSFQSD   650
 651  KVTIVDHHSATESFIKHMENEYRCRGGCPADWVWIVPPMSGSITPVFHQE   700
 701  MLNYRLTPCFEYQPDPWNTHVWKGTNGTPTKRRAIGFKKLAEAVKFSAKL   750
 751  MGQAMAKRVKATILYATETGKSQAYAKTLCEIFKHAFDAKVMSMEEYDIV   800
 801  HLEHETLVLVVTSTFGNGDPPENGEKFRCALMEMRHPNSLQEERKSYKVR   850
 851  FNSVSSYSDSRKSSGDGPDVRDHFESAGPLANVRFSVFGLGSRAYPHFCA   900
 901  FGHAVDTLLEELGGERILKMREGDELCGQEEAFRTWAKKVFKAACDVFCV   950
 951  GDDVNIEKANNSLISNDRSWKRNKFRLTYVAEAPGLTQGLSSVHKKRVSA  1000
1001  ARLLSRQNLQSPKSSRSTIFVRLHTNGSQELQYQPGDHLGVFPGNHEDLV  1050
1051  NALIERLEDAPPANQMVKVELLEERNTALGVISNWKDEPRLPPCTVFQAF  1100
1101  KYYLDITTPPTPLQLQQFASLASNEKEKQRLLVLSKGLQEYEEWKWGKNP  1150
1151  TIVEVLEEFPSIQMPATLLLTQLSLLQPRYYSISSSPDMYPDEVHLTVAI  1200
1201  VSYHTRDGEGPIHHGVCSSWLNRIPADEVVPCFVRGAPSFRLPRNPQVPC  1250
1251  ILVGPGTAFAPFRSFWQQRQFDIQHKGMSPCPMVLVFGCRQSKIDHIYRE  1300
1301  EALQAKNKGVFRELYTAYSREPDKPKKYVQDILQEQLAEQVYRALKEQGG  1350
1351  HIYVCGDVTMAADVLKAVQRIMAQQGKLSAEDAGVFISRLRDDNRYHEDI  1400
1401  FGVTLRTYEVTNRLRSESIAFIEESKKDTDEVFSS                 1435

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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