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

NucPred

Fetching P14248 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MTVDLNIPYSACELKRVKRLELGVLDPEIIKKISVCEIVNVDIYKDGFPR    50
  51  EGGLNDIRMGTIDYRTLCGTCNMNVKYCPGHFGHIELAKPMYHYGFMNVV   100
 101  LNVLRCVCYHCGRLLCNVNSSKVKYIEKIKVNSLRLRKLAELCLGIRACD   150
 151  HSVEEEGLNINDNSLNNFYNNDLSNLNMNQQMLLNKSNYTNIFEMVSKED   200
 201  VDCGCVQPKYSREGPNMYIQFLHSSEEDIDESKRKLSAEEALEILKKIRK   250
 251  EEMSILGFNSDRCVPASLILTCIPIPPPCARPYVQYGNQRSEDDLTLKLL   300
 301  DIVKTNIQLKRQTDRGAKSHVLQDLCSLLQFHITTLFDNDIPGMPIATTR   350
 351  SKKPIKAIRTRLKGKEGRLRGNLMGKRVDFSARTVITGDPNLNIDYIGVP   400
 401  KSVAMTLTFCETVTPLNYDNLKKLVERGPYEWPGAKYIIRDNGTKYDLRH   450
 451  VRRNSEKELEYGYKVERHMTDEDYILFNRQPSLHKMSIMGHKAKILPYST   500
 501  FRLNLSVTSPYNADFDGDEMNLHLAQSHETRSEIKHLMIVQRQIVSPQGN   550
 551  KPVMGIVQDSLLAIRKFTRRDNFLTKEEVMSLLIWIPYWNHVIPTPAIIK   600
 601  PRALWTGKQIFSMLLQFDDMNIEDDKNDTANNKVGRDVNTNVNKDSSKMN   650
 651  TSGNYYYGNSTNDNTDDYLEKGNAYSRSGNNHPNSPLSIGDNINVGNVQQ   700
 701  NDMSSPNNNNNNNNNNNSNNNNNNNIGGGINSFKRFNMVKINLMRDSSTS   750
 751  SKDDNPYCSINDGKVIIKNNELLSGIICKRTVGSSSGSLIHVLWHEMGPD   800
 801  KTKDFLSALQKVTNNWLEYVGFTVSCSDIIASNKVLGKVREILDKSKSEV   850
 851  SKLVEKAQKGELECQPGKSLYESFETRVNNELNCAREMAGKVASESLDER   900
 901  NNIFSMVASGSKGSIINISQIISCVGQQNVEGKRIPFGFNHRSLPHFIKF   950
 951  DYGPESRGFVSNSYLSGLTPQEVFFHAMGGREGIIDTACKTSETGYIQRR  1000
1001  LIKAMEDVMVQYDRTVRNSYGDIIQFLYGEDGMAGEYIEDQIIDLMKLDN  1050
1051  KEINKLYKYNFDEEPFGKDYYIGNKNDGSRNTTYIDYNKQNILNQEFEEL  1100
1101  YKCKNYLCKEIFPDGDIRQHLPINMNRLIEYAKSQFPCIPFVSNNNSTNN  1150
1151  NNNNNNNNNISNSRKLMDKGNLSSTHNHKENKKRRKRRRRKNKFDKFKNE  1200
1201  NNELMSEIKKEYENNDLNNMMISKGDQSPFKGMNEFHMGVADNDMGSDLG  1250
1251  NNNNYNNDDFVDDDYVDDDDYDDDDYDDDDYDDDDLDDDENYSDNINIGG  1300
1301  NRKYYGNTLKNNYDENSMLNPIDVVHKVNNFLEKLVIIKQINSNDTLSVE  1350
1351  AQNNATILLKAHLRTYLNSKLLTQTHKVSVKGLDWLLQEIEKIFYKSLCH  1400
1401  PGECVGALAAQSIGEPATQMTLNTFHFAGVGSKNVTLGVPRLKELINIVK  1450
1451  NVKTPSTTIYLDDMVSNDQQKAKDILTKLEYTTLKQLTSHAQIIYDPNTT  1500
1501  TTILEEDKSWVNEFYEFPDEDDTQYSLGEWVLRIQLTNIHVNEKKLTMKE  1550
1551  IVYIIYSVFSSDELDIIYTDDNSEDLVLRIRVKYLNGEYNFMNYDVVDNA  1600
1601  NEQVDEQEEDEEHLVANDRGNYDETKNSTHPHHDYNNNTTNIFKSKVKNN  1650
1651  ISSDINTKNEDSISINSSNNEQVKNINSSPVSNNMHNNNNNNNNDSSNIN  1700
1701  DIKVKNIKKEDGNEGALRGGGDSNTSALFGNKNSQKEDNIVNNNNDNNDD  1750
1751  DDEEEEEEDFLFGDHNVSPKNTKDGKNKNTNNKSNNNENKNKKSGNNNSN  1800
1801  NSNTYDDGDVDNDNDDDNDDNKSDITIKEDNDVAFMKTSTKNAEEDLELK  1850
1851  NKNHIEHNISREDTEDTFLKKLMEQCLSTLKLRGIENITKVYMREESKIT  1900
1901  YDSDNGKFVRSSHWVLDTDGCNLENIFCAPQVDFKKTVSNDIVEIFEVLG  1950
1951  IEAVRRALLKELRTVISFDSSYVNYRHLSILCDVMTQKGYLMSITRHGIN  2000
2001  RVDKGPLIKCSFEETVEILLEAAAFAQVDNLRGITENIMLGQLCKIGTGS  2050
2051  FDIIIDNQKLNDANQNLETIQDLTSAGFTTPDSLHVITPDGLQSPVAINT  2100
2101  INSPLPFSPTYNANLLSPTAPIDNVNNLLSPQYNLQNYGDNVMSPTSKDI  2150
2151  NNLDTLKLGGKFSPTQSPKSPTSVMHSPFSPFDHQNQQPVDATNLLFSPK  2200
2201  NNNIMNYNVFSPKPNINNNVIQSPNIYSPNPMLDIFSPKPQINHNIYSPS  2250
2251  YSPTSPTYNANNAYYSPTSPKNQNDQMNVNSQYNVMSPVYSVTSPKYSPT  2300
2301  SPKYSPTSPKYSPTSPKYSPTSPKYSPTSPKYSPTSPKYSPTSPKYSPTS  2350
2351  PVAQNIASPNYSPYSITSPKFSPTSPAYSISSPVYDKSGVVNAHQPMSPA  2400
2401  YILQSPVQIKQNVQDVNMFSPIQQAHVDEAKNDDPFSPMPYNIDEDEMKE  2450
2451  NM                                                  2452

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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