 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P56369 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MRIEKEIKNLLTTRNFSSEKNQTQFLRIQNWFSTHRLNSRQKNKNSEIKI 50
51 STFFACLPLALGFSCFLFKKNDIFLEGQGKASKASSFFQTNLPVFKTYHP 100
101 KLTFETFEYIVKPTALETQTEGSPMIFTPSKKKDFFEKKKNKNDVVLNQN 150
151 SFFGQPTFVGTIKKSPKPQQDVLQLVEETLFNKSEGISSFLLAENKETVL 200
201 EQATKKFSGFSCDSYTISSKKLSLVSSSASKLSKSLSASFLKAFMLDEFP 250
251 SYLQGLNPKSSSFSSDKGVLITKSPALKVFSKKKYKVEVKSSKVKGQKSE 300
301 SDKHLTFFLESTKLLKKLTLVNSKPSPLILFKKEAKNDISNKIVLSPAQK 350
351 DFSYQTRFSSKQPSEKAKAVSVVVKSVKDSNLLDQKTYKNDFLKEKLPLK 400
401 NKSWKPFLLSKKLSIKTCVENTYYKNQKEFSIDAIQLQAEFQKVFIEKKI 450
451 SYPFLEEAKALNPQIKTFELFNIKNPFLKQCWSIFFQNEMKNRDRNGISG 500
501 DFTQSILDQEKVQNNELFLDDTSEKILQNLEKVQVWNDSNGVRAMSGYIY 550
551 PDTNTRDLEWFLNLQKTFTRERVEPFFFQEKRPFKVNSGIKKATAFFPSL 600
601 KKERKNSQLLGVEKTNLSPLEILSKVSFPSRTTNYSFSVKPFPQIFIKTR 650
651 ESFLTHPETKKIIYDGPSVILDSKKNFDWSTKHQTNLQLWFQKYVSPLNP 700
701 LVQFQGNFFCEESVEKISQIFSSDREKKREKSEITAFLPLKLGKNAKCEI 750
751 DWFYDSELVESFFAPSISSLQIPSEKEQPDAFLNQENIRGMYLTLSEPED 800
801 PNKVEVFFPLLELKQPSFTNSIKQSKRFCHKTSFFENGYSSFFEFGVKGN 850
851 PDFDFSGVFNDQKQFAKKTASGNYRKTLSFFSKNQEKTSLFVQNWEPLNA 900
901 TSWLAVSQLSFAIFSFRVLKSLSDNYGRELLGYLMDLVAALGVLDDSLKQ 950
951 QIQILTGERQTGFRVFLESRKKFTDIVGIQKVLLELYEIVLFLRNSGRNF 1000
1001 THSETLPHGILLTGPPGTGKTLLVQALAGEAQVPVIVLSGSSLMEPGESA 1050
1051 AFKLQLVFQEARQLAPCIVFIDEIDTLSSKRSQLLQNPMANDPGFESFLE 1100
1101 SFLLQSKPSQSVKKTESFFGKFKNGAKKEFDNFKKQKKNPAEYNSKQNEK 1150
1151 QVSLLSQLLIELDGIQGRNGVVIFGATNRPEVLDPALLRPGRFDKIVKVG 1200
1201 LPAQKKRVEILQFYGQTLGYQKTMPWAYFGERTVGFTAADLATLMNESAL 1250
1251 KAILNQSNHTIETLEHGIERLTTSESEKYTVLKKEKEFKNKTTTPLLNSS 1300
1301 RIYSLRLAYYQAGKLLLSYALETHPKTMRASLWPRRPTLRSLAITANLEK 1350
1351 SLFEFARLWELTERIIGCYAGKAAEFLFLCKFSSTGLSEISTLGLEDQVF 1400
1401 AQKLVYFMLENCHFYSKKNAIQQAMKMSPNSNLKELRKKPEKLDLYSELL 1450
1451 NTIQFPPMWEASERETSSLTLQKNKEHSGIGFEDQIRYSSPWWQEDVSAE 1500
1501 MEFKPKNPGKGSRLYLYDYERTSRNPEWVPPDEFYHNSSGLKDIKNAFVT 1550
1551 LSDQKLYSVEKATQNKRKELGKVLAAGFSKKENEGTKNIKKSSAPKASFT 1600
1601 KNNVFCEWNEVSKLTRDYPAHSLLLQSFNKALVILNQNREILDRIVVELL 1650
1651 YQEILKKPQIDDLMKELENSKPKTEPNVFSTELQFDASKKAPFVELSWGF 1700
1701 QSRKPIPRWIDFAAVKGETT 1720
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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