 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8C3F2 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MGVQGFQEFLEKRCPGAVVPVDLLKLARTVSRQQQQQHLHRQLPPAALAP 50
51 GAPRITRGSAPLPPPPLPPAAFGAYSGGAGPSRHHHPAHHFHHHGQAPPG 100
101 LHPPPPPPLPGARVLVDAGSALPRLYGGYQTDWVCGGQWNAMLGYLSALC 150
151 QACAYPGGDGLELVVMFPGGLGKDRLAEWGRRCQAERQTAQLIVGHVGNK 200
201 GTPPPRAWFLPPACLSHCVRLALIRFRVKVFQSLEDHHLEVVAFFRENGF 250
251 HGLLAHDSEYALYNIPSYYSSHALKLSWNGKNLTTNQFLMQEVAKQLGLK 300
301 RMNFPIFAALLGNHILPDEDLAAFHWSLLGPEHPLASLKVRAHQLVLPPC 350
351 DVVIKAVSEYVSSIKDPSNLDVVGKDVFKQSQSRTEDKIERFKKAVEYYS 400
401 VTTKLSSLPVGPSFLGFRNNRLGNPPLPRNQMGPISPGKPMFSRQVPQKM 450
451 KYPPPFPMGPNSSLLFSHSVGESHAFSEDAMLQDNSFANWAVSYDSNTSQ 500
501 FPNCLTSKTSPPLGPDSSHSSSSDGDEANGAGSEQITEAVQQQPGWEDPN 550
551 GDRGAWGQPADAGVSETTVAESEPHIPSLLSMSTRNHMDITIPPLPPVAP 600
601 EVLRVAEHRHRRGLMYPYIYHVLTKGEIKIPVCIEDECNMELPPAALLFR 650
651 SARQYVYGVLFSLAETQRKMERLAIRRRLPMEVPSVILKEWSAYKGKSPQ 700
701 TPELVSALTFREWTCPNLKKLWLGKAVEDKNRRMRAFLACMKSDTPSMLN 750
751 PANVPTHLLLMCCVLRYMVQWPGGRILHRHELDTFLAQAVSTQLYEPDQL 800
801 QELKIEKLDARGIQLAALFMSGVDTALFANDACGQPVPWEHCCPWIYFDG 850
851 KLFQSKLIKAGRERVSLVELCDGQADLASKVEKMRQSILEGVNMNHPPPS 900
901 ALLPSPTFVPPMVPSLYPVSLYSRAMGSFPPPPQARSRGFAGLHPIPPQG 950
951 GKLEIAGMVVGQWAGSRSSRSRGSFGMQVVSVGGPGKGHGKEQAGRGSKG 1000
1001 HKKGNKQGSSDVISKAVELHQSRARSQVNGNNGTLIVEEKSDPLPAPSQC 1050
1051 ALSRDSNECNNSDDHCLPVKNGEKNHVPEQELEAVAQQKEE 1091
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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