 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NK54 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MQPQSDKQSASRLATTTSHSTAAASATAATPPKVKVIKSKRPLCHFKFYL 50
51 DICDHQLAKRIESDIKALGGHLEFFLSDDITHFVTDKPEVIGGTSGTPGT 100
101 PSTPGTPTSHYQQNDGSARKPNQRQSRADAILSRVRRSTVGVVNSGNSTP 150
151 TTSLKRSYTIWQTDYAQRFIKRIQTELKQYLEGKKEGGGGSTSASPHHIQ 200
201 LKKQYVKIESVKRNYRPYYHLIKQPDDWPKIDLSSEDGAFRLLTKSKTKD 250
251 KEHSMTRKPLGSRTSQKDKQAAGEAKPLQHPSLQELKKQSAIPNSPRSNC 300
301 REPIDSSEKQGGVCEICKLEYDILNIHLQSKDHELFAKNSDNFLALDTLI 350
351 QSSADVNRFLEEEPVESELDMDVDESLSNEELQSPRQRPSPALREKSKRI 400
401 TKGKHSSEKFQGVAVASPQTPFPGAKKVQGNSPGSLSELQRQEHPTTAAA 450
451 TPTTNSGRRKTQNSGLSPPKRAMLPPSSIYKVVETREECATPPRGRGRPP 500
501 NQVDSPSLIVKFQKIRQTELQRLNGEAENFMFPRTAVPTTRSSSELPTDV 550
551 DRQTTSDVRGRYSISSASLDTSTSEAETKESSGLPTSIRKRAQAVGRRRK 600
601 VGGAAAQDVFQRQLSTGSSSSNSNQQRFPSAPIQPEEGPQPQPKPQLKIK 650
651 IKQEQLVATRKSSRTATAIVTAATASSHQQQQLRQTTCRKMANKLEDRMG 700
701 ELVKPKIKIKKEVIEEQKVKELEDLEEILDKELDEEVDSSCSSGSDEDYI 750
751 AGSQRRITAAPRKSTDTREQRAARRLSRLTINRSAGELELTEVKTSPSKS 800
801 RTKIQKPSSPTKNKVKQTKAVPPAIDLFFDCSKSERLREMQYTFESLPSG 850
851 ELWNRVFLRQDAGEENYYTYYGSTNYRKLPYEMGPIPMAKTLPAHSCALC 900
901 REASEVKQDKGEQIKLEDQKPAPKKEVKKEEEVQSSSSSATYKNKKLHLL 950
951 QRYQQEQEQLQQLEGNSLATAGAKCDSKASTPELLEREFASGSMGDRVQL 1000
1001 IERVRSTSSSSCSNSQRSGITCRNKQLARIAELPPRKSPREHASTLALVS 1050
1051 CIIRQRQDSQSKTNSEAEEPPPPVAAPKLKTPIKQEPVAPSSPRTTRSQA 1100
1101 ATPVEELRFATEISETVKRMRRGQNKYDHSPPAPVPTPATSSPVRSRRLT 1150
1151 PAARNQSQIYSRRLEFATSQRESSASALLGKRKRRVNPSVAGTVRPTTQN 1200
1201 LPGTGAYRGVRKLPSKKGLLEYEMETCALKALDQARQYCNPGFVAWQLDK 1250
1251 YLELAGKEYDIEFDQISPEVESEGREERLVNTPQTPPPTDCFTSEFDLCD 1300
1301 LIMGSAGSGDDDEDVSRGNPPGSGRRMSNLNLYASYYRKRKSLKSNRTGW 1350
1351 PKAQRRRNAGGLGGSRALPDERINFQKMGLAELHPIKQEPMETEEEQTTT 1400
1401 TTTTTTTSATRGNLLSKDDEDDEGGGNSPSGGSPADDKQNSREDAVMTPP 1450
1451 ATDVDEQAEPQADEMESLPDEDETMADSVDQQQDVEAEIEATDADVEEEE 1500
1501 EEEDEDEDVFEDAYEEQDMGIQKTEPHEKRARIPSISVTTPPEDSSQGKK 1550
1551 LLLTLHNGQRLQATSTPSTGQVQQHQRRTPQLNGSLGSCISPSEKLGDNS 1600
1601 DIFTVSSDGLDTDLDLSNTQAGDSHEHCPHQTTPKRKFDISKYAPPNSGK 1650
1651 AASSCAAEAATAAVKSLAISQFLKKETCASSSSMRNAWRRTQRRAISAAC 1700
1701 ISAAPSARVPN 1711
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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