 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NX05 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MGVQGFQEFLEKRCPGAVVPVDLLKLARTVSRQQQQQHLHRQLPPTAALA 50
51 PGAPRAARGSVPLQPPLPPAALGAYSGGAGPTRHHHPAHHFHHHGQAQPG 100
101 LHPPLPPPPPPQLPGARVLVDAGSALPRLYGGYQTDWVCGGQWNAMLGYL 150
151 SALCQACAYPGGDGLELVVMFPGGLGKDRLAEWGRRCQAERQTAQLIVGH 200
201 VGNKGTPPPRAWFLPPACLSHCVRLALIRFRVKVFQSLEDHHLEVVAFFR 250
251 ENGFHGLLAHDSEYALYNIPSYYSSHALKLSWNGKNLTTNQFLMQEVAKQ 300
301 LGLKRMNFPIFAALLGNHILPDEDLAAFHWSLLGPEHPLASLKVRAHQLV 350
351 LPPCDVVIKAVSEYVSSIKDPSNLDVVGKDVFKQSQSRTEDKIERFKKAV 400
401 EYYSVTTKLSSLPVGPSFLGFRNNRLGNPPLPRNQVGTISAGKPMFSHQV 450
451 PQKVKYPPPFPVGPNSSLLFSSHALGESHAFSEDPMLQNSPFANWAVSYD 500
501 SSASQFPNYLPSKASPPLGPDSSHSSSSDGDEPNGASSDHITEAFHHQPE 550
551 WGNPNRDRGSWAQPVDTGVSEASLGDGEPHIPSLLSMSTRNHMDITIPPL 600
601 PPVAPEVLRVAEHRHRRGLMYPYIYHVLTKGEIKIPVCIEDECNMELPPA 650
651 ALLFRSARQYVYGVLFSLAETQRKMERLAMRRRLPVEVPSVILKEWSAYK 700
701 GKSPQTPELVSALTFREWTCPNLKKLWLGKAVEDKNRRMRAFLACMKSDT 750
751 PSMLNPANVPTHLLLMCCVLRYMVQWPGGRILHRHELDTFLAQAVSTQLY 800
801 EPDRLQELKIEKLDARGIQLAALFMSGVDTALFANDACGQPVPWEHCCPW 850
851 IYFDGKLFQSKLIKAGRERVSLVELCDGQADLATKVEKMRQSILEGVNMN 900
901 HPPPSALLPSPTFVPPMVPSLYPVSLYSRAMGSMPLPPQGRSRGFAGLHP 950
951 IPPQGGKLEIAGMVVGQWAGSRSSRGRGSFGMQVVSVGGPGKGHGKEQTG 1000
1001 RGSKGHKKGNKQGSSDGVSKSLELHQGRSRSQVNGNSGALIKEEKSDHRL 1050
1051 PAPSQCALSRDSNECNNGNRYLPMNNREKNHLQEQKLETVAQRKED 1096
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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