 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9W0S9 from www.uniprot.org...
The NucPred score for your sequence is 0.76 (see score help below)
1 MEHTASLPGYVREKLAELDLELSEGDITQKGYEKKRAKLLQPFLKKPEGD 50
51 KVKSTPPPPYYNVKNANNSTNHGNINNDGVIVSSEGYSYVTEVPSLSSSQ 100
101 QRHSKKIDFHQQAAMSLSSAPQSGNAGAPGYENMRPQGGAVGDPGYQNTR 150
151 EPSAFQNQQSTNNSQHRQRRTQRKVTHNEKRYHSEVRQEAVQQALAALKG 200
201 RPKPSLPMPSKRTSVLNRSPGCNDELDSSTDDESIPEETISPDKEYNYPR 250
251 DHISNSILPPEPIIKPPIRESSMGSQQHARTDVKQNQITNQKYTAPNSAP 300
301 ERRPPQNLPPLPTSEPLSSDYPPIAYKRENDFSDKAFKQKQYNAPDITQF 350
351 NNAHRAADRVTRYVNVSQNELNETDANGKWKVSAKIQQLLNTLKRPKRRP 400
401 LPEFYEDNDIELEIAANTKDPNAPKPEGSTMTPVQGEQLSIPAGLPRTLE 450
451 CALQRYGTNSFKSPMATVLDPNGKVTTTLTYGKLLSRAQKIAHALSTKIF 500
501 SKGPEQVTLKPGDRVALVYPNNDPLSFITAWYGCMFRGLVPLPIELPLSS 550
551 SDTPPQQVGFLLSSCGITVALTSEACLKGLPKSTTTGEIAKLKGWPRLQW 600
601 FVTEHLPKPPKEFNVGNLRADDSAAAYIEYTTDKEGSVMGVTVTRAAMIN 650
651 HCRALTMACHYTEGETIVCVLDFKREVGLWHSVLTSVLNGMHVIFIPYAL 700
701 MKLRPSSWMQLITKHRASCCLVKSRDLHWGLLATKDHKDISLSSLRMLLV 750
751 ADGANPWSLSSCDQFLSVFQAKGLRSDAICPCASSSEVFTVSLRRPGRGS 800
801 CGFSPSATGRGVLSMAALSHGVVRVDSEDSLTSLTLQDCGQVMPAAQMVV 850
851 VRSEGPPVLCKTDQVGEICVTSGSTSASYFGLDGMTNSTFKVQPLLEELE 900
901 QPKDGNGTVNIISKPIGEDFYVRSGLLGFLGPGGLVFVCGSRDGLMTVTG 950
951 RKHNADDIIATVLAVEPMRFIYRGRIAVFSIKVLRDERVCVIAEQRPDCS 1000
1001 EEESFQWMSRVLQAVDSIHQVGIYCLALVPPNHLPKTPLGGIHLCEARRR 1050
1051 FLEGSLHPANVLMCPHTCVTNLPKPRELHQGVQTAAKLSSSSGCGITDTG 1100
1101 VGPASVMVGNLVQGNRLAEAHGRDVGLAEDCERKPQLITGVLRWRANTSP 1150
1151 DHIIFTLLNSKGAIAKTLTCSELHKRAEKIAALLQERGRIEPGDHVALIF 1200
1201 PPGLDLLCAFYGCLYLGAIPITIRPPHPQNLNTTLPTVRMIVDVSKSGIV 1250
1251 LSIQPIIKLLKSREAATSIDPKTWPPILDIDDNPKRKYAGIATVSFDSSA 1300
1301 YLDFSVSTCGRLSGVNITHRSLSSLCASLKLACELYPSRHVALCLDPYCG 1350
1351 LGFVMWTLIGVYSGHHSILIAPYEVEANPSLWLSTLSQHRVRDTFCSYGV 1400
1401 IELCTKALSNSIPSLKQRNIDLRCVRTCVVVAEERPRVQLTQQFCKLFQA 1450
1451 LGLNTRCVSTSFGCRVNPAICVQGASSAESAQVYVDMRALRNNRVALVER 1500
1501 GAPNSLCVIESGKLLPGVKVIIANPETKGHCGDSHLGEIWVQAPHNANGY 1550
1551 FTIYGDETDYNDHFNAKLVTGATSELYARTGYLGFLRRTECSQSASLLDE 1600
1601 TTPSVASRDSDTESLNSISQLQLNFSNVSLGGNSEHSLVGGASNANDQEL 1650
1651 HDAVYVVGAVDEVISLRGMNYHPIDIENSVMRCHKKIAECAVFTWTNLLV 1700
1701 VVVELDGNESEALDLVPLVTNTVLEDHQLIVGVVVVVDPGVVPINSRGEK 1750
1751 QRMHLRDGFLADQLDPIYVAYNM 1773
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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