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

NucPred

Fetching P38931 from www.uniprot.org...

The NucPred score for your sequence is 0.83 (see score help below)

   1  MSSDASTYRLEDVLSSFYRVEKIKKINYHQYISKAQNDQWSIQMEFMLRK    50
  51  QDPKTLVALLSRDLWCFSINDDPVPTPPAIEHKPVSPDKIGTFTADYSKP   100
 101  NLPPHYALFLKALRRKIYINLALGSHNKLIQFGNACISLSGVPNYLVQLE   150
 151  PHLFVNGDLTVSLCAKNMGLVPMKEENLEESFLSKHALYLAPSGIRMHLA   200
 201  PASKQGYLITPPKHTELLLTTLSVSHGINLQNKKNLKWVAVVPDLGHLNG   250
 251  HTPTIASYLTPLLEAKKLVWPLHLIFAQPVADIENSTSGDPSEFHCLQDA   300
 301  LDAIDDFIQLKQTAAYRTPGSSGVLSSNIAGTNPLSSDGAYTEQFQHYKN   350
 351  NSISSQPASYHSVQETNKISPKDFSPNFTGIDKLMLSPSDQFAPAFLNTP   400
 401  NNNINENELFNDRKQTTVSNDLENSPLKTELEANGRSLEKVNNSVSKTGS   450
 451  VDTLHNKEGTLEQREQNENLPSDKSDSMVDKELFGEDEDEDLFGDSNKSN   500
 501  STNESNKSISDEITEDMFEMSDEEENNNNKSINKNNKEMHTDLGKDIPFF   550
 551  PSSEKPNIRTMSGTTKRLNGKRKYLDIPIDEMTLPTSPLYMDPGAPLPVE   600
 601  TPRDRRKSVFAPLNFNPIIENNVDNKYKSGGKFSFSPLQKEEALNFDISM   650
 651  ADLSSSEEEEDEEENGSSDEDLKSLNVRDDMKPSDNISTNTNIHEPQYIN   700
 701  YSSIPSLQDSIIKQENFNSVNDANITSNKEGFNSIWKIPQNDIPQTESPL   750
 751  KTVDSSIQPIESNIKMTLEDNNVTSNPSEFTPNMVNSEISNLPKDKSGIP   800
 801  EFTPADPNLSFESSSSLPFLLRHMPLASIPDIFITPTPVVTISEKEQDIL   850
 851  DLIAEQVVTDYNILGNLGIPKIAYRGVKDCQEGLITTTMLQLFSTFDRLN   900
 901  GNDTISKFYNMKQPYVFVKKHHELIKVKHDSQPFIKFLNFRPPNGIKNFK   950
 951  SLLLSSSFKEDCLSFAPTLSQTYINQELGFCELLKLTNEDPPGLMYLKAF  1000
1001  DKNKLLLLAAQIVSYCSNNKNSIKNVPPILIILPLDNATLTELVDKANIF  1050
1051  QVIKNEVCAKMPNIELYLKVIPMDFIRNVLVTVDQYVNVAISIYNMLPPK  1100
1101  SVKFTHIAHTLPEKVNFRTMQQQQMQQQQQQQQQQQNNSTGSSSIIYYDS  1150
1151  YIHLAYSRSVDKEWVFAALSDSYGQGSMTKTWYVGNSRGKFDDACNQIWN  1200
1201  IALNLASKKFGKICLILTRLNGILPDDELMNWRRLSGRNIHLAVVCVDDN  1250
1251  SKISFIDEDKLYPSFKPIYKDTRFGGRMDMTRLYDYEIRDIDQDIHGIVF  1300
1301  QHPFPLAHSQHRCAIRSGALIKFKKCDGDTVWDKFAVNLLNCPHSDSTQL  1350
1351  LETILEEFRNLAALNVWYGLSDGEDGHIPWHILAVKKMMNTLVHTRVKIA  1400
1401  NTSAATVHTATSSSIILSDK                                1420

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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