| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P38144 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MAYMLAIANFHFFKFYTRMRKKHENNSCNEKDKDENLFKIILAIFLQEKK 50
51 KYDCISSGSIMTASEEYLENLKPFQVGLPPHDPESNKKRYLLKDANGKKF 100
101 DLEGTTKRFEHLLSLSGLFKHFIESKAAKDPKFRQVLDVLEENKANGKGK 150
151 GKHQDVRRRKTEHEEDAELLKEEDSDDDESIEFQFRESPAYVNGQLRPYQ 200
201 IQGVNWLVSLHKNKIAGILADEMGLGKTLQTISFLGYLRYIEKIPGPFLV 250
251 IAPKSTLNNWLREINRWTPDVNAFILQGDKEERAELIQKKLLGCDFDVVI 300
301 ASYEIIIREKSPLKKINWEYIIIDEAHRIKNEESMLSQVLREFTSRNRLL 350
351 ITGTPLQNNLHELWALLNFLLPDIFSDAQDFDDWFSSESTEEDQDKIVKQ 400
401 LHTVLQPFLLRRIKSDVETSLLPKKELNLYVGMSSMQKKWYKKILEKDLD 450
451 AVNGSNGSKESKTRLLNIMMQLRKCCNHPYLFDGAEPGPPYTTDEHLVYN 500
501 AAKLQVLDKLLKKLKEEGSRVLIFSQMSRLLDILEDYCYFRNYEYCRIDG 550
551 STAHEDRIQAIDDYNAPDSKKFVFLLTTRAGGLGINLTSADVVVLYDSDW 600
601 NPQADLQAMDRAHRIGQKKQVKVFRLVTDNSVEEKILERATQKLRLDQLV 650
651 IQQNRTSLKKKENKADSKDALLSMIQHGAADVFKSGTSTGSAGTPEPGSG 700
701 EKGDDIDLDELLLKSENKTKSLNAKYETLGLDDLQKFNQDSAYEWNGQDF 750
751 KKKIQRDIISPLLLNPTKRERKENYSIDNYYKDVLNTGRSSTPSHPRMPK 800
801 PHVFHSHQLQPPQLKVLYEKERMWTAKKTGYVPTMDDVKAAYGDISDEEE 850
851 KKQKLELLKLSVNNSQPLTEEEEKMKADWESEGFTNWNKLEFRKFITVSG 900
901 KYGRNSIQAIARELAPGKTLEEVRAYAKAFWSNIERIEDYEKYLKIIENE 950
951 EEKIKRVKMQQEALRRKLSEYKNPFFDLKLKHPPSSNNKRTYSEEEDRFI 1000
1001 LLMLFKYGLDRDDVYELVRDEIRDCPLFELDFYFRSRTPVELARRGNTLL 1050
1051 QCLEKEFNAGIVLDDATKDRMKKEDENGKRIREEFADQTANEKENVDGVE 1100
1101 SKKAKIEDTSNVGTEQLVAEKIPENETTH 1129
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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