 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9FEC4 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MKADLATAKGSSPAFSAPRTYRARLLSRCLNKCFNTVLVSGGAAESRFRG 50
51 GATVGKAGAHDARGVGDLVDFLQQEATPYEVNVPPYLILPPLKSNEATTH 100
101 RRAGDSGGQGPAAAGGRGQARHGRRQAAASAATTVSAAPQTGATKPAATA 150
151 KTTPQRPRGSDADAGSRAQSQYGFGDPPGGGALKGAVDAASDAAPDVAAA 200
201 SPAPAGISDQLSTPACPPEREPQAGKPRASGRAPAAPGVGPQDVGGGSGA 250
251 CAPAPDESHMGLTHRDQGHDERISQTAGEAWKAGAVAAPPAAPTPSPPGL 300
301 AAAPTRLASSALGTHSSDGDMRRAVPGRDTPSLSAVAGPVTLSGSSSSSS 350
351 GRNSSSNSNTSTSSTSNGVTITSNVGVNGASPQERLMAARRAVVTMQWNT 400
401 HLGRRGRSFAPLPTGGMSIATSAASSSTSSASSSSSMNDGSNAKKTSDAA 450
451 VSLPVGQQPAAEQPHVPTAPGGPSQTGASAVAAQAPSSAMPTAAMAATMG 500
501 SATIGSAATLPTAAVVSSAAAEGTQPSGLLLAGGRPALLGRTIQGRIARL 550
551 QAAREALRAARHARVGAAMQPPPVQARPVQGQSGQVPQVGQGPVQSQPGR 600
601 RQEPAASATKLHVADGLPARPVQPAVSATDLQTDTATAASAPFPVSDASL 650
651 GSTEPLAASAPTTSLASASGPAIGTSSSNAHSSAAASEAAAGTVRAPTDT 700
701 AAPAASPAATAPALASTPFATPAAAPLPEPPEVVAARDLLGRLSRYQPAG 750
751 RDDGPAVLAPHARYSPAAYQAAAAAAAAQPQLLLAPLSLPQLAAVVAGYA 800
801 AAGHRHEPLLEALAGVALAKAGGAGGIGGGAAGAVPRGQAASELKRSRLT 850
851 FRAACVFLTALARLGYRGGAVTRLAAALAVWLARQLNTGAVTPRAKWKGT 900
901 WLAAALWAYATLEQLPAAAPTPPPPPASAAAASTAPRAAESRPAAAPAPA 950
951 EATATRTPLLTAPQLAPQRASASPDLELARGGVLLFTEAAEAVRVAPGWL 1000
1001 HLMDGREALWSLWAFRKAAAAYGRGEGTASGAVYVAAAGGYAMLQSGGAG 1050
1051 GGGMGQAGGAGRGGAGAGAAALPLVVAAPRYEANPLVELKLADRATSLFP 1100
1101 QLDPGQLAEAHVLLLECGLAEDELPQALTALRRCVIARADSIRPQPLAVM 1150
1151 VATLAVMQVRDVVWLSALAMACRNKMINMSPDQIVAVLHAFGSVLRFHHL 1200
1201 LLFHAAAVVCSCPGMWRLGGMGAGEVLRLVGAFAATRHYEGRLLRAAAER 1250
1251 MLQLGSTGSTAGQRAGLLQSLCSLHYRHNGLLRIVVADTFGLADLSPGSA 1300
1301 GQPRNMGSSAKLAGAGTAAAAGAAAPGLPPSLLVAVAEACGQLQHRPPGL 1350
1351 LQALHASRAAVWPRVGLAQRATLCWALLVLTGGLPAQYLPADRPRDAKRH 1400
1401 VRQSAAAAAAAAAAAQDQRQEQHQQHQQEQLLAKALVEYLQALGAGVQRW 1450
1451 PPPAPSSYHLQLLVACTVLASCTPPPAPAHMQQQPQSSGTGCQKSRRRRM 1500
1501 RYRRSRGAVLQQQLKEELDKLPASAMQRALEVQRRARSAALGGWAHEVAS 1550
1551 VVREVLQEASVDARADSEGRQPLPPHWLGQPPATLLSAAVSTGVEVCDGA 1600
1601 MLVDVAVELEVEAGLPRPQVKGRGRGRRTAARATTDVQGAEQAVVTEEAA 1650
1651 YEHSHPLRQRLQLALDLCPLPPPPPRTAAPVLSAAYAPGAGGAGTSATAE 1700
1701 VTANRTTGAPRSLAVGAAAGGAVIRNSRWLLSGAGALRRRLLTHAGWLVV 1750
1751 PVRERQWKDLRSAEQQRRVVREWLKAVLLHAQQ 1783
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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