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

NucPred

Fetching Q19127 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MKQLLIFCLLFGSIFHHGDAGCIMRGLCQKHTENAYGPCVTNDTNVEPTA    50
  51  FDKTHPAYEKMVEFCPHLLTGDNKLCCTPSQAEGLTKQIAQARHILGRCP   100
 101  SCFDNFAKLWCEFTCSPNQQDFVSISEMKPIEKKEGFTPEYQPAEAYVNT   150
 151  VEYRLSTDFAEGMFSSCKDVTFGGQPALRVMCTSTPCTLTNWLEFIGTQN   200
 201  LDLNIPIHTKFLLYDPIKTPPSDRSTYMNVNFTGCDKSARVGWPACSTSE   250
 251  CNKEEYANLIDLDDGKTSGQTCNVHGIACLNIFVMLAFIGSLAVLLCVGF   300
 301  VFTSYDEDYTNLRQTQSGEESPKRNRIKRTGAWIHNFMENNARDIGMMAG   350
 351  RNPKSHFFIGCAVLIFCLPGMIYHKESTNVVDMWSSPRSRARQEEMVFNA   400
 401  NFGRPQRYQQIMLLSHRDFQSSGKLYGPVFHKDIFEELFDILNAIKNIST   450
 451  QDSDGRTITLDDVCYRPMGPGYDCLIMSPTNYFQGNKEHLDMKSNKEETV   500
 501  SEDDDAFDYFSSEATTDEWMNHMAACIDQPMSQKTKSGLSCMGTYGGPSA   550
 551  PNMVFGKNSTNHQAANSIMMTILVTQRTEPEIQKAELWEKEFLKFCKEYR   600
 601  EKSPKVIFSFMAERSITDEIENDAKDEIVTVVIALAFLIGYVTFSLGRYF   650
 651  VCENQLWSILVHSRICLGMLSVIINLLSSFCSWGIFSMFGIHPVKNALVV   700
 701  QFFVVTLLGVCRTFMVVKYYAQQRVSMPYMSPDQCPEIVGMVMAGTMPAM   750
 751  FSSSLGCAFSFFIGGFTDLPAIRTFCLYAGLAVLIDVVLHCTIFLALFVW   800
 801  DTQRELNGKPEFFFPYQIKDLLGAYLIGRQRATDTFMTQFFHFQVAPFLM   850
 851  HRMTRIITGIIFIASFITTVILSSKISVGFDQSMAFTEKSYISTHFRYLD   900
 901  KFFDVGPPVFFTVDGELDWHRPDVQNKFCTFPGCSDTSFGNIMNYAVGHT   950
 951  EQTYLSGEMYNWIDNYLEWISRKSPCCKVYVHDPNTFCSTNRNKSALDDK  1000
1001  ACRTCMDFDYVANSYPKSSIMYHRPSIEVFYRHLRHFLEDTPNSECVFGG  1050
1051  RASFKDAISFTSRGRIQASQFMTFHKKLSISNSSDFIKAMDTARMVSRRL  1100
1101  ERSIDDTAHVFAYSKIFPFYEQYSTIMPILTTQLFITVVGVFGIICVTLG  1150
1151  IDVKGAACAVICQVSNYFHIVAFMYIFNIPVNALSATNLVMSSGILIEFS  1200
1201  VNVLKGYACSLRQRAKDRAESTVGSIGPIILSGPVVTMAGSTMFLSGAHL  1250
1251  QIITVYFFKLFLITIVSSAVHALIILPILLAFGGSRGHGSSETSTNDNDE  1300
1301  QHDACVLSPTAESHISNVEEGILNRPSLLDASHILDPLLKAEGGIDKAID  1350
1351  IITIDRSYPSTPSSLPCTSRMPRAHIEPDLRSL                   1383

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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