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

NucPred

Fetching Q12674 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MGIADGQRRRSSSLRTQMFNKHLYDKYRGRTDDEIELEDINESKTFSGSD    50
  51  NNDKDDRDETSGNYAAEEDYEMEEYGSPDVSYSIITKILDTILDRRRTFH   100
 101  SKDGRHIPIILDHNAIEYKQAATKRDGHLIDERFNKPYCDNRITSSRYTF   150
 151  YSFLPRQLYAQFSKLANTYFFIVAVLQMIPGWSTTGTYTTIIPLCVFMGI   200
 201  SMTREAWDDFRRHRLDKEENNKPVGVLVKDGNNDAQEVYTLPSSVVSSTA   250
 251  YLTKSAAAENNPPLNDDRNSSQGHFLDTHFNNFELLKNKYNVHIHQKKWE   300
 301  KLRVGDFVLLTQDDWVPADLLLLTCDGENSECFVETMALDGETNLKSKQP   350
 351  HPELNKLTKAASGLANINAQVTVEDPNIDLYNFEGNLELKNHRNDTIMKY   400
 401  PLGPDNVIYRGSILRNTQNVVGMVIFSGEETKIRMNALKNPRTKAPKLQR   450
 451  KINMIIVFMVFVVATISLFSYLGHVLHKKKYIDQNKAWYLFQADAGVAPT   500
 501  IMSFIIMYNTVIPLSLYVTMEIIKVVQSKMMEWDIDMYHAETNTPCESRT   550
 551  ATILEELGQVSYIFSDKTGTLTDNKMIFRKFSLCGSSWLHNVDLGNSEDN   600
 601  FEDNRDNTNSLRLPPKAHNGSSIDVVSIGDQNVLDRLGFSDAPIEKGHRP   650
 651  SLDNFPKSRNSIEYKGNSSAIYTGRPSMRSLFGKDNSHLSKQASVISPSE   700
 701  TFSENIKSSFDLIQFIQRYPTALFSQKAKFFFLSLALCHSCLPKKTHNES   750
 751  IGEDSIEYQSSSPDELALVTAARDLGYIVLNRNAQILTIKTFPDGFDGEA   800
 801  KLENYEILNYIDFNSQRKRMSVLVRMPNQPNQVLLICKGADNVIMERLHD   850
 851  RELAAKKMADICTSTKERKDAEAELVLQQRKSLERMVDEEAMARTSLRNS   900
 901  LSSVPRASLSLQAVRKSLSMKNSRTRDPEKQIDSIDQFLETVKKSDQEIG   950
 951  SVVNKSRKSLHKQQIEKYGPRISIDGTHFPNNNVPIDTRKEGLQHDYDTE  1000
1001  ILEHIGSDELILNEEYVIERTLQAIDEFSTEGLRTLVYAYKWIDIGQYEN  1050
1051  WNKRYHQAKTSLTDRKIKVDEAGAEIEDGLNLLGVTAIEDKLQDGVSEAI  1100
1101  EKIRRAGIKMWMLTGDKRETAINIGYSCMLIKDYSTVVILTTTDENIISK  1150
1151  MNAVSQEVDSGNIAHCVVVIDGATMAMFEGNPTYMSVFVELCTKTDSVIC  1200
1201  CRASPSQKALMVSNIRNTDPNLVTLAIGDGANDIAMIQSADIGVGIAGKE  1250
1251  GLQASRVSDYSIGQFRFLLKLLFVHGRYNYIRTSKFMLCTFYKEITFYFT  1300
1301  QLIYQRYTMFSGSSLYEPWSLSMFNTLFTSLPVLCIGMFEKDLKPMTLLT  1350
1351  VPELYSYGRLSQGFNWLIFMEWVILATTNSLIITFLNVVMWGMSSLSDNT  1400
1401  MYPLGLINFTAIVALINVKSQFVEMHNRNWLAFTSVVLSCGGWLVWCCAL  1450
1451  PILNNTDQIYDVAYGFYNHFGKDITFWCTSLVLALLPITLDIVYKTFKVM  1500
1501  IWPSDSDIFAELEQKSDIRKKLELGAYSEMRQGWTWDKDPSTFTRYTDKV  1550
1551  LSRPRTNSRASAKTHNSSIYSMSNGNVDHSSKKNFFGNSSKKSSERYEVL  1600
1601  PSGKLIKRPSLKTQSSKDSIGGNITTKLTKKLKLPSRNVEDEDVNQIIQA  1650
1651  RLKDLE                                              1656

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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