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

NucPred

Fetching Q04690 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MAAHRPVEWVQAVVSRFDEQLPIKTGQQNTHTKVSTEHNKECLINISKYK    50
  51  FSLVISGLTTILKNVNNMRIFGEAAEKNLYLSQLIILDTLEKCLAGQPKD   100
 101  TMRLDETMLVKQLLPEICHFLHTCREGNQHAAELRNSASGVLFSLSCNNF   150
 151  NAVFSRISTRLQELTVCSEDNVDVHDIELLQYINVDCAKLKRLLKETAFK   200
 201  FKALKKVAQLAVINSLEKAFWNWVENYPDEFTKLYQIPQTDMAECAEKLF   250
 251  DLVDGFAESTKRKAAVWPLQIILLILCPEIIQDISKDVVDESNINKKLFL   300
 301  DSLRKALAGHGGSRQLTESAAIACVKLCKASTYINWEDNSVIFLLVQSMV   350
 351  VDLKNLLFNPSKPFSRGSQPADVDLMIDCLVSCFRISPHNNQHFKICLAQ   400
 401  NSPSTFHYVLVNSLHRIITNSALDWWPKIDAVYCHSVELRNMFGETLHKA   450
 451  VQGCGAHPAIRMAPSLTFKEKVTSLKFKEKPTDLETRSYKCLLLSMVKLI   500
 501  HADPKLLLCNPRKQGPETQSSTAELITGLVQLVPQSHMPEVAQEAMEALL   550
 551  VLHQLDSIDLWNPDAPVETFWEISSQMLFYICKKLTSHQMLSSTEILKWL   600
 601  REILICRNKFLLKNKQADRSSCHSLYLYGVGCEMSATGNTTQMSVDHDEF   650
 651  LRACTPGASLRKGRGNSSMDSTAGCSGTPPICRQAQTKLEVALYMFLWNP   700
 701  DTEAVLVAMSCFRHLCEEADIRCGVDEVSVHNFLPNYNTFMEFASVSNMM   750
 751  STGRAALQKRVMALLRRIEHPTAGNIEAWEDTHAKWEQATKLILNYPKAK   800
 801  MEDGQAAESLHKTIVKRRMSHVSGGGSIDLSDTDSLQEWINMTGFLCALG   850
 851  GVCLQQRSSSGLATYSPPMGAVSERKGSMISVMSSEGNIDSPVSRFMDRL   900
 901  LSLMVCNHEKVGLQIRTNVKDLVGLELSPALYPMLFNKLKNTISKFFDSQ   950
 951  GQVLLSDSNTQFVEQTIAIMKNLLDNHTEGSSEHLGQASIETMMLNLVRY  1000
1001  VRVLGNMVHAIQIKTKLCQLVEVMMARRDDLSFCQEMKFRNKMVEYLTDW  1050
1051  VMGTSNQAADDDIKCLTRDLDQASMEAVVSLLAGLPLQPEEGDGVELMEA  1100
1101  KSQLFLKYFTLFMNLLNDCSEVEDENAQTGGRKRGMSRRLASLRHCTVLA  1150
1151  MSNLLNANVDSGLMHSIGLGYHKDLQTRATFMEVLTKILQQGTEFDTLAE  1200
1201  TVLADRFERLVELVTMMGDQGELPIAMALANVVPCSQWDELARVLVTLFD  1250
1251  SRHLLYQLLWNMFSKEVELADSMQTLFRGNSLASKIMTFCFKVYGATYLQ  1300
1301  KLLDPLLRVIITSSDWQHVSFEVDPTRLEPSESLEENQRNLLQMTEKFFH  1350
1351  AIISSSSEFPSQLRSVCHCLYQATCHSLLNKATVKERKENKKSVVSQRFP  1400
1401  QNSIGAVGSAMFLRFINPAIVSPYEAGILDKKPPPRIERGLKLMSKVLQS  1450
1451  IANHVLFTKEEHMRPFNDFVKSNFDLARRFFLDIASDCPTSDAVNHSLSF  1500
1501  ISDGNVLALHRLLWNNQEKIGQYLSSNRDHKAVGRRPFDKMATLLAYLGP  1550
1551  PEHKPVADTHWSSLNLTSSKFEEFMTRHQVHEKEEFKALKTLSIFYQAGT  1600
1601  SKAGNPIFYYVARRFKTGQINGDLLIYHVLLTLKPYYAKPYEIVVDLTHT  1650
1651  GPSNRFKTDFLSKWFVVFPGFAYDNVSAVYIYNCNSWVREYTKYHERLLT  1700
1701  GLKGSKRLIFIDCPGKLAEHIEHEQQKLPAATLALEEDLKVFHNALKLAH  1750
1751  KDTKVSIKVGSTAVQVTSAERTKVLGQSVFLNDIYYASEIEEICLVDENQ  1800
1801  FTLTIANQGTPLTFMHQECEAIVQSIIHIRTRWELSQPDSIPQHTKIRPK  1850
1851  DVPGTLLNIALLNLGSSDPSLRSAAYNLLCALTCTFNLKIEGQLLETSGL  1900
1901  CIPANNTLFIVSISKTLAANEPHLTLEFLEECISGFSKSSIELKHLCLEY  1950
1951  MTPWLSNLVRFCKHNDDAKRQRVTAILDKLITMTINEKQMYPSIQAKIWG  2000
2001  SLGQITDLLDVVLDSFIKTSATGGLGSIKAEVMADTAVALASGNVKLVSS  2050
2051  KVIGRMCKIIDKTCLSPTPTLEQHLMWDDIAILARYMLMLSFNNSLDVAA  2100
2101  HLPYLFHVVTFLVATGPLSLRASTHGLLINIIHSLCTCSQLHFSEETKQV  2150
2151  LRLSLTEFSLPKFYLLFGISKVKSAAVIAFRSSYRDRSFSPGSYERETFA  2200
2201  LTSLETVTEALLEIMEACMRDIPTCKWLDQWTELAQRFAFQYNPSLQPRA  2250
2251  LVVFGCISKRVSHGQIKQIIRILSKALESCLKGPDTYNSQVLIESTVIAL  2300
2301  TKLQPLLNKDSPLHKALFWVAVAVLQLDEVNLYSAGTALLEQNLHTLDSL  2350
2351  RIFNDKSPEEVFMAIRNPLEWHCKQMDHFVGLNFNSNFNFALVGHLLKGY  2400
2401  RHPSPAIVARTVRILHTLLTLVNKHRNCDKFEVNTQSVAYLAALLTVSEE  2450
2451  VRSRCSLKHRKSLLLTDISMENVPMDTYPIHHGDPSYRTLKETQPWSSPK  2500
2501  GSEGYLAATYPAVGQTSPRARKSMSLDMGQPSQANTKKLLGTRKSFDHLI  2550
2551  SDTKAPKRQEMESGITTPPKMRRVAETDYEMETQRIPSSQQHPHLRKVSV  2600
2601  SESNVLLDEEVLTDPKIQALLLTVLATLVKYTTDEFDQRILYEYLAEASV  2650
2651  VFPKVFPVVHNLLDSKINTLLSLCQDPNLLNPIHGIVQSVVYHEESPPQY  2700
2701  QTSYLQSFGFNGLWRFAGPFSKQTQIPDYAELIVKFLDALIDTYLPGIDE  2750
2751  ETSEESLLTPTSPYPPALQSQLSITANLNLSNSMTSLATSQHSPGLDKEN  2800
2801  VELSPTAGHCNSGRTRHGSASQVQKQRSAGSFKRNSIKKIV           2841

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.