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

NucPred

Fetching Q9UKE5 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MASDSPARSLDEIDLSALRDPAGIFELVELVGNGTYGQVYKGRHVKTGQL    50
  51  AAIKVMDVTGDEEEEIKQEINMLKKYSHHRNIATYYGAFIKKNPPGMDDQ   100
 101  LWLVMEFCGAGSVTDLIKNTKGNTLKEEWIAYICREILRGLSHLHQHKVI   150
 151  HRDIKGQNVLLTENAEVKLVDFGVSAQLDRTVGRRNTFIGTPYWMAPEVI   200
 201  ACDENPDATYDFKSDLWSLGITAIEMAEGAPPLCDMHPMRALFLIPRNPA   250
 251  PRLKSKKWSKKFQSFIESCLVKNHSQRPATEQLMKHPFIRDQPNERQVRI   300
 301  QLKDHIDRTKKKRGEKDETEYEYSGSEEEEEENDSGEPSSILNLPGESTL   350
 351  RRDFLRLQLANKERSEALRRQQLEQQQRENEEHKRQLLAERQKRIEEQKE   400
 401  QRRRLEEQQRREKELRKQQEREQRRHYEEQMRREEERRRAEHEQEYIRRQ   450
 451  LEEEQRQLEILQQQLLHEQALLLEYKRKQLEEQRQAERLQRQLKQERDYL   500
 501  VSLQHQRQEQRPVEKKPLYHYKEGMSPSEKPAWAKEVEERSRLNRQSSPA   550
 551  MPHKVANRISDPNLPPRSESFSISGVQPARTPPMLRPVDPQIPHLVAVKS   600
 601  QGPALTASQSVHEQPTKGLSGFQEALNVTSHRVEMPRQNSDPTSENPPLP   650
 651  TRIEKFDRSSWLRQEEDIPPKVPQRTTSISPALARKNSPGNGSALGPRLG   700
 701  SQPIRASNPDLRRTEPILESPLQRTSSGSSSSSSTPSSQPSSQGGSQPGS   750
 751  QAGSSERTRVRANSKSEGSPVLPHEPAKVKPEESRDITRPSRPASYKKAI   800
 801  DEDLTALAKELRELRIEETNRPMKKVTDYSSSSEESESSEEEEEDGESET   850
 851  HDGTVAVSDIPRLIPTGAPGSNEQYNVGMVGTHGLETSHADSFSGSISRE   900
 901  GTLMIRETSGEKKRSGHSDSNGFAGHINLPDLVQQSHSPAGTPTEGLGRV   950
 951  STHSQEMDSGTEYGMGSSTKASFTPFVDPRVYQTSPTDEDEEDEESSAAA  1000
1001  LFTSELLRQEQAKLNEARKISVVNVNPTNIRPHSDTPEIRKYKKRFNSEI  1050
1051  LCAALWGVNLLVGTENGLMLLDRSGQGKVYNLINRRRFQQMDVLEGLNVL  1100
1101  VTISGKKNKLRVYYLSWLRNRILHNDPEVEKKQGWITVGDLEGCIHYKVV  1150
1151  KYERIKFLVIALKNAVEIYAWAPKPYHKFMAFKSFADLQHKPLLVDLTVE  1200
1201  EGQRLKVIFGSHTGFHVIDVDSGNSYDIYIPSHIQGNITPHAIVILPKTD  1250
1251  GMEMLVCYEDEGVYVNTYGRITKDVVLQWGEMPTSVAYIHSNQIMGWGEK  1300
1301  AIEIRSVETGHLDGVFMHKRAQRLKFLCERNDKVFFASVRSGGSSQVFFM  1350
1351  TLNRNSMMNW                                          1360

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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