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

NucPred

Fetching O42130 from www.uniprot.org...

The NucPred score for your sequence is 0.73 (see score help below)

   1  MELLDSPAPLRPLHDNPRLPKADGAQKRLSVERIYQKKTQLEHILLRPDT    50
  51  YIGSVETVTQQMWVFDEDVGLNCRDVTFVPGLYKIFDEILVNAADNKQRD   100
 101  KSMSCIKVTIDPENNTISVWNNGKGIPVVEHKVEKVYVPALIFGQLLTSS   150
 151  NYDDDEKKVTGGRNGYGAKLCNIFSTKFTVETACREYKKLFKQTWTDNMG   200
 201  KAGEMTLKHFDGEDYTCVTFQPDLSKFKMTILDKDIVALMSRRAYDIAGS   250
 251  TKDVKVFLNGKRLPVKGFRSYVDLYLKDKVDETGNALKVIHEEVNSRWEV   300
 301  CLTLSEKGFQQVSFVNSIATTKGGRHVDYVADQIVTKLIDVVKKKNKNGV   350
 351  GVKPFQVKNHMWIFVNSLIENPTFDSQTKENMTLQAKSFGSTCKLSEKFI   400
 401  KGAVGCGIVESILNWVKFKAQTQLNKKCSAVKHTKIKGVPKLDDANDAGS   450
 451  KNSIDCTLILTEGDSAKTLAVSGLGVVGRDKYGVFPLRGKMLNVREASHK   500
 501  QIMENAEINNIIKIVGLQYKKNYEDRESLKSLRYGKIMIMTDQDQDGSHI   550
 551  KGLLINFIHHNWPSLLRHNFLEEFITPIIKVSKNKEEIPFYSIPEFEEWK   600
 601  SSTQNYNSWKIKYYKGLGTSTSKEAKEYFADMARHRIGFKYSGPEDDAAI   650
 651  TLAFSKKKVEERKEWLTNFMEDRRQRNVHGLPEDYLYGKDTNYLTYNDFI   700
 701  NKELVLFSNSDNERSIPSLVDGLKPGQRKVLFTCFKRNDKREVKGAQLAG   750
 751  SVAEMSSYHHGEASLMMTIINLAQNFVGSNNLNLLQPIGQFGTRLHGGKD   800
 801  SASPRYIFTMLSPLARLLFPPVDDNVLRFLYDDNQRVEPEWYMPIIPMVL   850
 851  INGAEGIGTGWSCKIPNFDIRETVNNIRCLLDGKEPLPMLPSYKNFKGTI   900
 901  DELGPNQYVISGEVSILDSTTIEITELPVRTWTQTYKEQVLEPMLNGTEK   950
 951  TPPLITDYKEYHTDTTVKFVVKMSEEKLAEAEAVGLHKVFKLQTNLTCNS  1000
1001  MVLFDHVGFLKKYESPQDILKEFFELRLRYYGLRKEWLIGMLGAESAKLN  1050
1051  NQARFILEKIDGKIVIENKPKKELIQVLIQRGYESDPVKAWKELQNKEEE  1100
1101  EGDESGEESAAATGPDFNYLLNMPLWYLTKEKKDELCKQRDNKDKELEDL  1150
1151  KHKSPSDLWKEDLAAFVEELDAVEAKQMQDEMAGITGKPLKVKGGKQGGK  1200
1201  QKVTKAQLAEVMPSPHGIRVVPRVTAEMKAEAEKRIKKKIKSEKNESDEK  1250
1251  QEGNSSGDKEPSSLKQRLAQKRKAEQGTKRQTTLPFKPIKKMKRNPWSDS  1300
1301  ESDSESDDFEVPSKRERVVRQAAAKIKPMVNSDSDADLTSSDEDSEYQEN  1350
1351  SEGNTDSDTTSKKKPPKAKAVPKEKKGKAPKEKPLPDAVPVRVQNVAAES  1400
1401  ASQDPAAPPVSVPRAQAVPKKPAAAKKGSTAKDNQPSIMDILTKKKAAPK  1450
1451  APRRAQREESPPSEATAAVAKKPGPPRGRKATKRLTSSSDSDSDFGSRPS  1500
1501  KSVAAKKSKRDDDDSYSIDLTADSPAAAAPRTRPGRLKKPVQYLESSDED  1550
1551  DMF                                                 1553

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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