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

NucPred

Fetching Q80TT8 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MVGERRAGNLLVPLGPRLQAYPEELLRQRPGHDGHPEYLIRWSVLKCSEE    50
  51  GKVSSEEEKTEHLLMWLSAPEVYANCPMLLRERPIPKGPQHEPAGEVGSF   100
 101  PRDPGGLDELAMTEMEADVRALVRRAARQLAEGGTSSLTAAVLHTVHVLS   150
 151  AYASIGPLTGVFRETGALDLLMHMLCNPEPQIRRSAGKMLQALAAHDAGS   200
 201  RAHVLLSLSQHDGIEQHMDFDSRYTLLELFAETTSTEEHCMALEGIHLPQ   250
 251  IPGKLLFSLVKRYLCVTSLLDQLNNSPESGAGDQSSPCLTKEKSRAQQEL   300
 301  EFSMAVGNLISELVRSMGWARNLSEQGALPPRPSRSIFQPCLSGPPPLLL   350
 351  PTIVTTPRKQGRAFRGRSEFSSRSGYGEYVQQTVQPGMRVRILDDYEEIS   400
 401  AGDEGEFQQSNNGVPPVQVFWQSTGRTYWVHWHMLEILGPEEATGDSASA   450
 451  AVEKGAGAAVLGTVCPSWDWKPTHGLYSLPYLQPEPQKNEEESGYLTQAE   500
 501  WWELLFFIKKLDVGEQQPIFQNLHEKLDEEALGEKALGELSVPIEMAEGV   550
 551  LQVLSNRFEGSNLCDLLNSRIYTKYGLLPKELGSLPSSRRHSCSPEPEEG   600
 601  SRSAANFSEKEEACRANAVPPEAEMELASAKTEPPKAQSDSQLFNQLLVT   650
 651  EGMTLPPETQEAATEMARALRGPGPRSSLDQHVAAVLATVQISSLDTNLQ   700
 701  LSGLCALSQAVEEVTERDHPLVRPDRPLREKLVKTLVDLLTNQVGEKMVV   750
 751  VMALRLLYLLMTKHEWRPLFAREGGIYAVLICMQEYKTSVLVQQAGLAAL   800
 801  KMLAIANSSDVPTFIPSRDSIQPLFDTQMTREIFASIDSATRPGSESLLL   850
 851  SVPAAVVLMLNTEGCSSAVRNGLLLLNLLLCNHHTLGDQIITQELRDTLF   900
 901  RHSGIAPGTEPMPTTRTILTMLLSRYSEPRGSPERAVLETPSTQGQDGSP   950
 951  ESLIRSLVGDLSAELFLDLERVLCHEGSPPAAVRPLLRRLQQETQPFLLL  1000
1001  LRTLDAPGPNRTLLLTILRVMTRLLDHPETMVLPWHEVLEPCLNCLNGPS  1050
1051  SDSEVVQEVTCFLHRLALMQKDYAVVLCCLGGKEALSKVLDKHSTQLLLA  1100
1101  SELRHLVAECEKYSQLCSNLTSSILAGCIQMVLGQIEDHRRTYKPITIPF  1150
1151  FDVFLRHLCQGSSVEVKEDRCWEKVEVSSNPHRASKLTDRNPKTYWESNG  1200
1201  STGSHSITLHMHRGVLIRQLTLLVASEDSSYMPARVVVFGGDNVGCISTE  1250
1251  LNTVNVMPSASRVTLLENLTRFWPIIQIRIKRCQQGGIDTRVRGVEVLGP  1300
1301  KPTFWPLFREQLCRRTCLFYTIRAQAWSRDIAEDRQRLLQLYPRLNRVLR  1350
1351  HEQNFADRFLPDDEAAQALGKTCWEALVSPLVQNITSPDAGGVSSLGWLL  1400
1401  DQYLEHRESTRSRQGPAASFASQVRRLCHLLVHVEAPPGPSPEPSSQPLS  1450
1451  KNSKGQDGSPTPAPTPVCPSTSLRNLTQCWLSVVQGQVSRFLAAAWRASD  1500
1501  FVPRYCSLYQRLQSAGSELFGPRAAFTLALRSGFSGALLQQSFLTAAHIS  1550
1551  EQFARHIDQQIHGGLLGGAAGVGMLGRLQRHLEPIMVLSGLELATTFEHF  1600
1601  YQHYMADRLLSLGSSWLEGAVLEQIGPCFPNRLPQLMLQSLHTSEELQHR  1650
1651  FHLFQLQQLDRQLLEQGDQEEWRPEKVEEDDEGQETGRELFTDPGPAISV  1700
1701  LVLSPRCWPVSPLCYLHHPRKHLQAELCDALERFSSFYSHSQNCPVLDIG  1750
1751  PHRRLQWTWLGRAELQFGDQTLHVSTVQMWLLLNFNQSEEVSVETLLRNS  1800
1801  DLSPELLHQALLPLTSDNGPLTLEETQDYPQGGVLRLREPRSQTHEEVLW  1850
1851  LIPPQTYLSVEKDEGRTLEQKRNLLSCLLVRILKAHREKGLHIDQLVCLV  1900
1901  LEAWQKGPDPPGRLGNAAAVGVACSSTDVLSCILHLLGQGYVERRDDRPQ  1950
1951  VLMYATPEPMGPCRGQADVPFCGNKNTETSRPSPEAVVALASLQLPAGRT  2000
2001  MSPQEVEGLMEQTVRQVQETLNLEPDVAQHLLAHSHWGTEQLLQSYSDDP  2050
2051  EPLLLAAGLRVPQAQVVPTRPDQCPVCVTPLGPHDDSPSLCCLHCCCKSC  2100
2101  WNEYLTTRIEQNFVLNCTCPIADCPAQPTGAFIRNIVSSPEVISKYEKAL  2150
2151  LRGYVESCSNLTWCTNPQGCDRILCRQGLGSGTTCSKCGWASCFSCSFPE  2200
2201  AHYPASCGHMSQWVDDGGYYDGMSVEAQSKHLAKLISKRCPSCQAPIEKN  2250
2251  EGCLHMTCARCNHGFCWRCLKSWKPSHKDYYNCSAMVSKAARQEKRFQDY  2300
2301  NERCTFHHQAREFAVNLRNQASAIQEVPPPKSFTFLQDACRALEQARKVL  2350
2351  AYACVYSFYSQDTEYMDVVEQQTENLELHTNALQILLEETLLRCRDLASS  2400
2401  LRFLRADCLSTGTELLRRIQERLLAILQHSTQDFRVGLQSPSVETREVKG  2450
2451  SNVPSDQPQGSSGLEVEDEEEEEEEEEEEEEEEEEDVPEWQHEFDEELDN  2500
2501  DSFSYDEESENLDRETFFFGDEDEDDESYD                      2530

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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