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

NucPred

Fetching P29475 from www.uniprot.org...

The NucPred score for your sequence is 0.57 (see score help below)

   1  MEDHMFGVQQIQPNVISVRLFKRKVGGLGFLVKERVSKPPVIISDLIRGG    50
  51  AAEQSGLIQAGDIILAVNGRPLVDLSYDSALEVLRGIASETHVVLILRGP   100
 101  EGFTTHLETTFTGDGTPKTIRVTQPLGPPTKAVDLSHQPPAGKEQPLAVD   150
 151  GASGPGNGPQHAYDDGQEAGSLPHANGLAPRPPGQDPAKKATRVSLQGRG   200
 201  ENNELLKEIEPVLSLLTSGSRGVKGGAPAKAEMKDMGIQVDRDLDGKSHK   250
 251  PLPLGVENDRVFNDLWGKGNVPVVLNNPYSEKEQPPTSGKQSPTKNGSPS   300
 301  KCPRFLKVKNWETEVVLTDTLHLKSTLETGCTEYICMGSIMHPSQHARRP   350
 351  EDVRTKGQLFPLAKEFIDQYYSSIKRFGSKAHMERLEEVNKEIDTTSTYQ   400
 401  LKDTELIYGAKHAWRNASRCVGRIQWSKLQVFDARDCTTAHGMFNYICNH   450
 451  VKYATNKGNLRSAITIFPQRTDGKHDFRVWNSQLIRYAGYKQPDGSTLGD   500
 501  PANVQFTEICIQQGWKPPRGRFDVLPLLLQANGNDPELFQIPPELVLEVP   550
 551  IRHPKFEWFKDLGLKWYGLPAVSNMLLEIGGLEFSACPFSGWYMGTEIGV   600
 601  RDYCDNSRYNILEEVAKKMNLDMRKTSSLWKDQALVEINIAVLYSFQSDK   650
 651  VTIVDHHSATESFIKHMENEYRCRGGCPADWVWIVPPMSGSITPVFHQEM   700
 701  LNYRLTPSFEYQPDPWNTHVWKGTNGTPTKRRAIGFKKLAEAVKFSAKLM   750
 751  GQAMAKRVKATILYATETGKSQAYAKTLCEIFKHAFDAKVMSMEEYDIVH   800
 801  LEHETLVLVVTSTFGNGDPPENGEKFGCALMEMRHPNSVQEERKSYKVRF   850
 851  NSVSSYSDSQKSSGDGPDLRDNFESAGPLANVRFSVFGLGSRAYPHFCAF   900
 901  GHAVDTLLEELGGERILKMREGDELCGQEEAFRTWAKKVFKAACDVFCVG   950
 951  DDVNIEKANNSLISNDRSWKRNKFRLTFVAEAPELTQGLSNVHKKRVSAA  1000
1001  RLLSRQNLQSPKSSRSTIFVRLHTNGSQELQYQPGDHLGVFPGNHEDLVN  1050
1051  ALIERLEDAPPVNQMVKVELLEERNTALGVISNWTDELRLPPCTIFQAFK  1100
1101  YYLDITTPPTPLQLQQFASLATSEKEKQRLLVLSKGLQEYEEWKWGKNPT  1150
1151  IVEVLEEFPSIQMPATLLLTQLSLLQPRYYSISSSPDMYPDEVHLTVAIV  1200
1201  SYRTRDGEGPIHHGVCSSWLNRIQADELVPCFVRGAPSFHLPRNPQVPCI  1250
1251  LVGPGTGIAPFRSFWQQRQFDIQHKGMNPCPMVLVFGCRQSKIDHIYREE  1300
1301  TLQAKNKGVFRELYTAYSREPDKPKKYVQDILQEQLAESVYRALKEQGGH  1350
1351  IYVCGDVTMAADVLKAIQRIMTQQGKLSAEDAGVFISRMRDDNRYHEDIF  1400
1401  GVTLRTYEVTNRLRSESIAFIEESKKDTDEVFSS                  1434

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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