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

NucPred

Fetching P47989 from www.uniprot.org...

The NucPred score for your sequence is 0.32 (see score help below)

   1  MTADKLVFFVNGRKVVEKNADPETTLLAYLRRKLGLSGTKLGCGEGGCGA    50
  51  CTVMLSKYDRLQNKIVHFSANACLAPICSLHHVAVTTVEGIGSTKTRLHP   100
 101  VQERIAKSHGSQCGFCTPGIVMSMYTLLRNQPEPTMEEIENAFQGNLCRC   150
 151  TGYRPILQGFRTFARDGGCCGGDGNNPNCCMNQKKDHSVSLSPSLFKPEE   200
 201  FTPLDPTQEPIFPPELLRLKDTPRKQLRFEGERVTWIQASTLKELLDLKA   250
 251  QHPDAKLVVGNTEIGIEMKFKNMLFPMIVCPAWIPELNSVEHGPDGISFG   300
 301  AACPLSIVEKTLVDAVAKLPAQKTEVFRGVLEQLRWFAGKQVKSVASVGG   350
 351  NIITASPISDLNPVFMASGAKLTLVSRGTRRTVQMDHTFFPGYRKTLLSP   400
 401  EEILLSIEIPYSREGEYFSAFKQASRREDDIAKVTSGMRVLFKPGTTEVQ   450
 451  ELALCYGGMANRTISALKTTQRQLSKLWKEELLQDVCAGLAEELHLPPDA   500
 501  PGGMVDFRCTLTLSFFFKFYLTVLQKLGQENLEDKCGKLDPTFASATLLF   550
 551  QKDPPADVQLFQEVPKGQSEEDMVGRPLPHLAADMQASGEAVYCDDIPRY   600
 601  ENELSLRLVTSTRAHAKIKSIDTSEAKKVPGFVCFISADDVPGSNITGIC   650
 651  NDETVFAKDKVTCVGHIIGAVVADTPEHTQRAAQGVKITYEELPAIITIE   700
 701  DAIKNNSFYGPELKIEKGDLKKGFSEADNVVSGEIYIGGQEHFYLETHCT   750
 751  IAVPKGEAGEMELFVSTQNTMKTQSFVAKMLGVPANRIVVRVKRMGGGFG   800
 801  GKETRSTVVSTAVALAAYKTGRPVRCMLDRDEDMLITGGRHPFLARYKVG   850
 851  FMKTGTVVALEVDHFSNVGNTQDLSQSIMERALFHMDNCYKIPNIRGTGR   900
 901  LCKTNLPSNTAFRGFGGPQGMLIAECWMSEVAVTCGMPAEEVRRKNLYKE   950
 951  GDLTHFNQKLEGFTLPRCWEECLASSQYHARKSEVDKFNKENCWKKRGLC  1000
1001  IIPTKFGISFTVPFLNQAGALLHVYTDGSVLLTHGGTEMGQGLHTKMVQV  1050
1051  ASRALKIPTSKIYISETSTNTVPNTSPTAASVSADLNGQAVYAACQTILK  1100
1101  RLEPYKKKNPSGSWEDWVTAAYMDTVSLSATGFYRTPNLGYSFETNSGNP  1150
1151  FHYFSYGVACSEVEIDCLTGDHKNLRTDIVMDVGSSLNPAIDIGQVEGAF  1200
1201  VQGLGLFTLEELHYSPEGSLHTRGPSTYKIPAFGSIPIEFRVSLLRDCPN  1250
1251  KKAIYASKAVGEPPLFLAASIFFAIKDAIRAARAQHTGNNVKELFRLDSP  1300
1301  ATPEKIRNACVDKFTTLCVTGVPENCKPWSVRV                   1333

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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