 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P97685 from www.uniprot.org...
The NucPred score for your sequence is 0.59 (see score help below)
1 MARQQAPPWVHVALILFLLSLGGAIEIPMDPSIQNELTQPPTITKQSVKD 50
51 HIVDPRDNILIECEAKGNPAPSFHWTRNSRFFNIAKDPRVSMRRRSGTLV 100
101 IDFRSGGRPEEYEGEYQCFARNKFGTALSNRIRLQVSKSPLWPKENLDPV 150
151 VVQEGAPLTLQCNPPPGLPSPVIFWMSSSMEPITQDKRVSQGHNGDLYFS 200
201 NVMLQDMQTDYSCNARFHFTHTIQQKNPFTLKVLTTRGVAERTPSFMYPQ 250
251 GTSSSQMVLRGMDLLLECIASGVPTPDIAWYKKGGDLPSDKAKFENFNKA 300
301 LRITNVSEEDSGEYFCLASNKMGSIRHTISVRVKAAPYWLDEPKNLILAP 350
351 GEDGRLVCRANGNPKPTVQWLVNGDPLQSAPPNPNREVAGDTIIFRDTQI 400
401 SSRAVYQCNTSNEHGYLLANAFVSVLDVPPRMLSPRNQLIRVILYNRTRL 450
451 DCPFFGSPIPTLRWFKNGQGSNLDGGNYHVYENGSLEIKMIRKEDQGIYT 500
501 CVATNILGKAENQVRLEVKDPTRIYRMPEDQVAKRGTTVQLECRVKHDPS 550
551 LKLTVSWLKDDEPLYIGNRMKKEDDSLTIFGVAERDQGSYTCMASTELDQ 600
601 DLAKAYLTVLADQATPTNRLAALPKGRPDRPRDLELTDLAERSVRLTWIP 650
651 GDDNNSPITDYVVQFEEDQFQPGVWHDHSKFPGSVNSAVLHLSPYVNYQF 700
701 RVIAVNEVGSSHPSLPSERYRTSGAPPESNPSDVKGEGTRKNNMEITWTP 750
751 MNATSAFGPNLRYIVKWRRRETRETWNNVTVWGSRYVVGQTPVYVPYEIR 800
801 VQAENDFGKGPEPETVIGYSGEDLPSAPRRFRVRQPNLETINLEWDHPEH 850
851 PNGILIGYTLRYVPFNGTKLGKQMVENFSPNQTKFSVQRADPVSRYRFSL 900
901 SARTQVGSGEAATEESPTPPNEATPTAAPPTLPPTTVGTTGLVSSTDATA 950
951 LAATSEATTVPIIPTVVPTTVATTIATTTTTTAAATTTTTTESPPTTTTG 1000
1001 TKIHETAPDEQSIWNVTVLPNSKWANITWKHNFRPGTDFVVEYIDSNHTK 1050
1051 KTVPVKAQAQPIQLTDLFPGMTYTLRVYSRDNEGISSTVITFMTSTAYTN 1100
1101 NQTDIATQGWFIGLMCAIALLVLILLIVCFIKRSRGGKYPVREKKDVPLG 1150
1151 PEDPKEEDGSFDYSDEDNKPLQGSQTSLDGTIKQQESDDSLVDYGEGGEG 1200
1201 QFNEDGSFIGQYTVRKDKEETEGNESSEATSPVNAIYSLA 1240
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.) |
Go back to the NucPred Home Page.