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

NucPred

Fetching Q29498 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MESHMFSVQQIQPNVISVRLFKRKVGGLGFLVKERVSKPPVIISDLIRGG    50
  51  AAEQSGLIQAGDIILAVNGQPLVDLSYDSALEVLRGIASETHVVLILRGP   100
 101  EGFTTHLETTFTGDGTPKTIRVTRPGRVTPPPDAPAGREQPRAVDGAPGP   150
 151  GNGPQHAPDPGQEASSLAQANGLAARPPGQDPAKKSTGVALQGSGENNKL   200
 201  LKEIEPVLNLLTSGGKAINGGGPAKTETKDVEVQVDRDPDSKSHKPLPLG   250
 251  VENDRVFNDLWGKGNMPVVLNNPYSEKEQPSASGKQSPTKNGSPSKCPRF   300
 301  LKVKNWETDVVLSDTLHLKSTLGTGCTEHICMGSVMLPSQQIRKPEDVRT   350
 351  KEQLFPLAKEFIDQYYSSIKRFGSKAHMERLEEVNKEIETTSTYQLKDTE   400
 401  LIYGAKHAWRNASRCVGRIQWSKLQVFDARDCTTAHGMFNYICNHIKYAT   450
 451  NKGNLRSAITIFPQRTDGKHDFRVWNSQLIRYAGYKQPDGSILGDPANVE   500
 501  FTEICIQQGWKPPRSRFDVLPLLLQANGNDPELFQIPPELVLEVPIRHPK   550
 551  FEWFKDLGLKWYGLPAVSNMLLEIGGLEFSACPFSGWYMGTEIGVRDYCD   600
 601  SSRYNILEDVAKKMNLDMRKTSSLWKDQALVEINIAVLYSFQSDKVTIVD   650
 651  HHSATESFIKHMENEYRCRGGCPADWVWIVPPMSGSITPVFHQEMLNYRL   700
 701  TPSFEYQPDPWNTHVWKGTNGTPTKRRAIGFKKLAEAVKFSAKLMGQAMA   750
 751  KRVKATILYATETGKSQAYAKTLCEIFKHAFDAKVMSMEEYDIVHLEHET   800
 801  LVLVVTSTFGNGDPPENGEKFGCALMEMRNPNSVHEERKYPEPLRFFPRK   850
 851  GPPLSRGDTEVHGLAAVRDSQLRSYKVRFNSVSSYSDSRKSSGDGPDLRD   900
 901  NFESTGPLANVRFSVFGLGSRAYPHFCAFGHAVDTLLEELGGERILKMRE   950
 951  GDELCGQEEAFRTWAKKVFKAACDVFCVGDDVNIEKANNSLISNDRSWKR  1000
1001  NKFRLTYVAEAPELTQGLSNVHKKRVSAARLLSRQNLQSPKSSRSTIFVR  1050
1051  LHTNGNQELQYQPGDHLGVFPGNHEDLVNALIERLEDAPPANQLVKVELL  1100
1101  EERNTALGVISNWTDEHRLPPCTIFQAFKYYLDITTPPTPLQLQQFASLA  1150
1151  TSEKERQRLLVLSKGLQEYEEWKWGKNPTIVEVLEEFPSIQMPSTLLLTQ  1200
1201  LSLLQPRYYSISSSPDMYPDEVHLTVAIVSYRTRDGEGPIHHGVCSSWLN  1250
1251  RIQADEVVPCFVRGAPSFHLPQNPQVPCILVGPGTGIAPFRSFWQQRQFD  1300
1301  IQHKGMSPCPMVLVFGCRQSKIDHIYREEALQAKSKGVFRELYTAYSREP  1350
1351  DKPKKYVQDILQEQLAEPVYRALKEQGGHIYVCGDVTMAADVLKAIQRIM  1400
1401  TQKGKLSVEDAGVFISRLRDDNRYHEDIFGVTLRTYEVTNRLRSESIAFI  1450
1451  EESKKDTDEVFSS                                       1463

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.