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

NucPred

Fetching P41516 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MELSPLQPVNENMLLNKKKNEDGKKRLSVERIYQKKTQLEHILLRPDTYI    50
  51  GSVELVTQQMWVYDEDVGINYREVTFVPGLYKIFDEILVNAADNKQRDPK   100
 101  MSCIRVTMMRNNLISIWNNGKGIPVVEHKVEKMYVPALIFGQLLTSSNYD   150
 151  DDEKKVTGGRNGYGAKLCNIFSTKFTVETASREYKKMFKQTWMDNMGRAG   200
 201  DMELKPFSGEDYTCITFQPDLSKFKMQSLDKDIVALMVRRAYDIAGSTKD   250
 251  VKVFLNGNRLPVKGFRSYVDMYLKDKVDETGNALKVVHEQVNPRWEVCLT   300
 301  MSEKGFQQISFVNSIATSKGGRHVDYVADQIVSKLVDVVKKKNKGGVAVK   350
 351  ADQVKNHMWIFGNAVIENPTFDSQTKENMTLQAKSFGSTCQLSEKFIKAA   400
 401  IGCGIVESILNWVKFKAQIQLNKKCSAVKHNRIKGIPKLDDANDAGSRNS   450
 451  AECTLILTEGDSAKTLAVSGLGVVGRDKYGVFPLRGKILNVREASHKQIM   500
 501  ENAEINNIIKIVGLQYKKNYEDEDSLKTLRYGKIMIMTDQDQDGSHIKGL   550
 551  LINFIHHNWPSLLRHRFLEEFITPIVKVSKNKQEIAFYSLPEFEEWKSTN   600
 601  PNHKKWKVKYYKGLGTSTSKEAKEYFANMKRHRIQFKYSGPEDDAAISLA   650
 651  FSKKQVDDRKEWLTNFMEDRRQRKLLGLPEDYLYGQTTMYLTYNDFINKE   700
 701  LILFSNSDNERSIPSMVDGLKPGQRKVLFTCFKRNDKREVKVAQLAGSVA   750
 751  EMSSYHHGEMSLMMTIINLAQNFVGSNNLNLLQPIGQFGTRLHGGKDSAS   800
 801  PRYIFTMLSPLARLLFPSKDDHTLRFLYDDNQRVEPEWYIPIIPMVLING   850
 851  AEGIGTGWSCKIPNFDVREVVNNIRRLLDGEEPLPMLPSYKNYKGTIEEL   900
 901  ASNQYVINGEVAILNSTTIEITELPIRTWTQTYKEQVLEPMLNGTEKTPP   950
 951  LITDYREYHTDTTVKFVIKMTEEKLAEAERVGLHKVFKLQTSLTCNSMVL  1000
1001  FDHVGCLKKYDTVLDILRDFFELRLKYYGLRKEWLLGMLGAESSKLNNQA  1050
1051  RFILEKIDGKIVIENKPKKELIKVLIQRGYDSDPVKAWKEAQQKVPEEEE  1100
1101  NEENEESESESTSPAAESGPTFNYLLDMPLWYLTKEKKDELCKQRDEKEQ  1150
1151  ELNTLKKKTPSDLWKEDLAAFVEELEVVEAKEKQDEQVGLPGKGVKAKGK  1200
1201  KAQISEVLPSPVGKRVIPQVTMEMRAEAEKKIRRKIKSENVEGTPAEDGA  1250
1251  EPGLRQRLEKRQKREPGTRAKKQTTLPFKPIKKAQKQNPWSDSESDMSSN  1300
1301  ESNFDVPPREKEPRIAATKAKFTADLDSDDDFSGLDEKDEDEDFFPLDDT  1350
1351  PPKTKMPPKNTKKALKPQKSSTSVDLESDGKDSVPASPGASAADVPAETE  1400
1401  PSKPSSKQTVGVKRTITKGQSLTSTAGTKKRAVPKETKSDSALNAHVSKK  1450
1451  PAPAKAKNSRKRMPSSSDSSDSEFEKAISKGATSKKLKGEERDFHVDLDD  1500
1501  TVAPRAKSGRARKPIKYLEESDDDLF                          1526

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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