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

NucPred

Fetching P01026 from www.uniprot.org...

The NucPred score for your sequence is 0.39 (see score help below)

   1  MGPTSGSQLLVLLLLLASSLLALGSPMYSIITPNVLRLESEETFILEAHD    50
  51  AQGDVPVTVTVQDFLKKQVLTSEKTVLTGATGHLNRVFIKIPASKEFNAD   100
 101  KGHKYVTVVANFGATVVEKAVLVSFQSGYLFIQTDKTIYTPGSTVFYRIF   150
 151  TVDNNLLPVGKTVVIVIETPDGVPIKRDILSSHNQYGILPLSWNIPELVN   200
 201  MGQWKIRAFYEHAPKQTFSAEFEVKEYVLPSFEVLVEPTEKFYYIHGPKG   250
 251  LEVSITARFLYGKNVDGTAFVIFGVQDEDKKISLALSLTRVLIEDGSGEA   300
 301  VLSRKVLMDGVRPSSPEALVGKSLYVSVTVILHSGSDMVEAERSGIPIVT   350
 351  SPYQIHFTKTPKFFKPAMPFDLMVFVTNPDGSPARRVPVVTQGSDAQALT   400
 401  QDDGVAKLSVNTPNNRQPLTITVSTKKEGIPDARQATRTMQAQPYSTMHN   450
 451  SNNYLHLSVSRVELKPGDNLNVNFHLRTDAGQEAKIRYYTYLVMNKGKLL   500
 501  KAGRQVREPGQDLVVLSLPITPEFIPSFRLVAYYTLIGANGQREVVADSV   550
 551  WVDVKDSCVGTLVVKGDPRDNRQPAPGHQTTLRIEGNQGARVGLVAVDKG   600
 601  VFVLNKKNKLTQSKIWDVVEKADIGCTPGSGKNYAGVFMDAGLTFKTNQG   650
 651  LQTDQREDPECAKPAARRRRSVQLMERRMDKAGQYTDKGLRKCCEDGMRD   700
 701  IPMPYSCQRRARLITQGESCLKAFMDCCNYITKLREQHRRDHVLGLARSD   750
 751  VDEDIIPEEDIISRSHFPESWLWTIEELKEPEKNGISTKVMNIFLKDSIT   800
 801  TWEILAVSLSDKKGICVADPYEITVMQDFFIDLRLPYSVVRNEQVEIRAV   850
 851  LFNYREQEKLKVRVELLHNPAFCSMATAKKRYYQTIEIPPKSSVAVPYVI   900
 901  VPLKIGLQEVEVKAAVFNHFISDGVKKILKVVPEGMRVNKTVAVRTLDPE   950
 951  HLNQGGVQREDVNAADLSDQVPDTDSETRILLQGTPVAQMAEDAVDGERL  1000
1001  KHLIVTPSGCGEQNMIGMTPTVIAVHYLDQTEQWEKFGLEKRQEALELIK  1050
1051  KGYTQQLAFKQPISAYAAFNNRPPSTWLTAMWSRSFSLAANLIAIDSQVL  1100
1101  CGAVKWLILEKQKPDGVFQEDGPVIHQEMIGGFRNTKEADVSLTAFVLIA  1150
1151  LQEARDICEGQVNSLPGSINKAGEYLEASYLNLQRPYTVAIAGYALALMN  1200
1201  KLEEPYLTKFLNTAKDRNRWEEPGQQLYNVEATSYALLALLLLKDFDSVP  1250
1251  PVVRWLNDERYYGGGYGSTQATFMVFQALAQYRADVPDHKDLNMDVSLHL  1300
1301  PSRSSPTVFRLLWESGSLLRSEETKQNEGFSLTAKGKGQGTLSVVTVYHA  1350
1351  KVKGKTTCKKFDLRVTIKPAPETAKKPQDAKSSMILDICTRYLGDVDATM  1400
1401  SILDISMMTGFIPDTNDLELLSSGVDRYISKYEMDKAFSNKNTLIIYLEK  1450
1451  ISHSEEDCLSFKVHQFFNVGLIQPGSVKVYSYYNLEESCTRFYHPEKDDG  1500
1501  MLSKLCHNEMCRCAEENCFMHQSQDQVSLNERLDKACEPGVDYVYKTKLT  1550
1551  TIELSDDFDEYIMTIEQVIKSGSDEVQAGQERRFISHVKCRNALKLQKGK  1600
1601  QYLMWGLSSDLWGEKPNTSYIIGKDTWVEHWPEAEERQDQKNQKQCEDLG  1650
1651  AFTETMVVFGCPN                                       1663

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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