 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VUM0 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MSKKLNTSVGGTPTNTLLNYFSKSPAFDKKKLTPSVKTDPDASKSEKENL 50
51 QNQQPKVKDGKKEASKPAAKRKLPISDDEPASGQRKRKRIVQPESDSEPE 100
101 MEVTKSEDDFSDCASDYEPDENEASDDSVSSGAEEVSPSENDMSVDSPTP 150
151 KKSRKKSKILNNNNNNEPSSKKVKLESTIQLAEGATFQEKLKNLQSNAKQ 200
201 DASYDDIVTNTSNLDEPVVWPHQKLEFLQPDKIKDKEGRRPDHPDYDKST 250
251 LHVPEKFLNGLSPGVRQWWVLKSDNYDCVLFFKVGKFYELYHMDADVGVN 300
301 ELGFTYMRGEFAHSGFPEISFDKMSTILVDRGFKVARVEQTETPDMMTER 350
351 CKRIKATKFDKVVAREICQITNRGTQVFGSQCKIGPNHQPNYMLAIVEKD 400
401 EGTCSRYGVCFIDTSIGDFHLGEFEDDKNCSRLLTLVSHHMPVLFLNEKS 450
451 ALSQRTQQIVRTVLGGILKEPVPGNGKHACSAEKTLKLLAERYYAGPGSD 500
501 DNWPLVLRTMQSDMDHLGLTPNDNYKLALKALGQCIFFIHKCKLEPKVLP 550
551 MARYQLYVPPDQLADAKPAVASTLRRSHMVLDATTLSNLRIIGEEHSLLS 600
601 TLDHCCTKFGKRLLHHWLCAPSCDVSVIKERQDAIGELIRMPTELQEVRA 650
651 LLAPMPDFERNLAQIHLFGNKQIKQMDHPDSRAILFEEKLYNKQKLQGFM 700
701 AVLKGFNDLTKLPTMFHQCKTTLLKRITQLPESGGSFPDLSKELQYFATA 750
751 FDHDAAAKTGVIAPQAGMDAEYDAAMDSIGEVEKRLKTYLVEQERHFGCR 800
801 ITYFGSDKKRYQLDVPESHASKANKSYTLEGQTKGKKPSRRYTTAETRAL 850
851 LKDMQHAEDTRNMVLKDLARRLFEKFSNHYDQWKQCIDCVANLDVLGSLA 900
901 EYAGQQMVICVPELVSDADQPFIQLEEGYHPCANASTYIPNGLELGTASE 950
951 APLSLLTGPNMGGKSTLMREVGLLVIMAQIGAHIPAASCRLSLVDRIFTR 1000
1001 LGAQDDILAGHSTFLVELNETSLILKHATCHSLVLLDELGRGTATYDGTA 1050
1051 IAASVVNFLANLKCRTLFSTHYHNLIDFFHNDKRITLGHMACMVENEDNA 1100
1101 DPTQETVTFLYKYTAGACPKSYGFNAAKLAGMPQGIIKRAYELSKKVEAI 1150
1151 ALQRKITAKIVAATAGNEDTKKEKINALKDLLKQLKMCQV 1190
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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