 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P08649 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MRLLWGLAWAFSFFASSLQKPRLLLFSPSVVNLGTPLSVGVQLLDAPAGQ 50
51 EVKGSVYLRNPTSGPCSPKKDFKLSSGNDFVLLRLEVPLKDVRSCGLFGL 100
101 RRAPHIQLVAHSPWLKNTASKATETQGVNLLFSSRRGHIFVQTDQPIYNP 150
151 GQRVRYRVFALDQKMRPSTDTLTVTVENSHGLRVRKKEVFAPTSIFQDDF 200
201 IIPDISEPGTWKISARFSDGLESNRSTHFEVKKYVLPNFEVKLTPWKPYI 250
251 LTVPSYREEIQLDVQARYVYGKPVQGVAYTRFALMDEQGKKSFLRGLETQ 300
301 TKLVEGQTHISISRDQFQAALGKVNTEIGDLEGLRLYAAVAVIESPGGEM 350
351 EEAELTSWPFVSSAFSLDLSHTKQHLVPGAPFLLQALVREMSGSEASDVP 400
401 VKVSATLLSGSDSKVLDFQQNTNGIGQVSFSIHVPPTITELRLLVSAGSL 450
451 YPAVAKLTVQAPPSRGPGFLSIEPLDLRSPRVGDTFVLSLRTVGIPMPTF 500
501 SHYYYMIISRGQIMAMSREPRRALTSISVLVDHHLAPSFYFVAYFYHQGL 550
551 PVANSLLINVQPGDCEGKLELKVDGAKEYRNGDSMKLQLQTDSEALVALG 600
601 AVDTALYAVGGRSHKPLDMSKVFEVMNSYNLGCGPGGGDDALQVFQTAGL 650
651 AFSDGDRLTQTKENLSCPKEKKSRQKRNVNFQKAISEKLGQYSSPDTKRC 700
701 CQDGMTKLPMARTCEQRAARVPQPACREPFLSCCKFAEDLRRNQTRSQAG 750
751 LARAQDMLQEEDLIDEDDILVRSFFPENWLWRVEPVDRSKLLTVWLPDSL 800
801 TTWEIHGVSLSKSKGLCVAKPTRVRVFREFHLHLRLPISVRRFEQLELRP 850
851 VLYNYLSEDVTVSVHVSPVEGLCLAGGGLLAQQVSVPAGSARPVAFSVVP 900
901 TAAASIPLKVVARGSFTIGDAVSKILQIEKEGAIHREEIVYNLDPLNNLG 950
951 RSLEIPGSSDPNVIPDGDFSSFVRVTASEPLETLGSEGALSPGGVASLLR 1000
1001 LPRGCAEQTMIYLAPTLTASHYLDRTEQWSKLPPETKDHAVDLIQKGHMR 1050
1051 IQQFRKKDGSFGAWLHRDSSTWLTAFVLKILSLAQEQIGDSPEKLQETAG 1100
1101 WLLGQQLDDGSFHDPCPVIHRGMQGGLVGTDETVALTAFVVIALHHGLAV 1150
1151 FQDENSQQLKKRVEASITKANSFLGQKASAGLLGAHASAITAYALTLTKA 1200
1201 SEDLQNVAHNSLMAMAEETGENLYWGSAIGSQDNVVSSTPAPRNPSEPVP 1250
1251 QAPALWIETTAYGLLHLLLREGKGEMADKVATWLTHQGSFQGGFRSTQDT 1300
1301 VVTLDALSAYWIASHTTEEKALNVTLSSMGRNGYKSHLLQLNNHQVKGLE 1350
1351 EELKFSLGSTINVKVGGNSKGTLKILRTYNVLDMKNTTCQDLRIEVTVTG 1400
1401 YVEYTREANEDYEYDYDMPAADDPSVHSQPVTPLQLFEGRRSRRRREAPK 1450
1451 AADEQESRVQYTVCIWRNGNLGLSGMAIADITLLSGFQALRADLEKLTSL 1500
1501 SDRYVSHFETDGPHVLLYFDSVPTTRECVGFGALQEVAVGLVQPASAVLY 1550
1551 DYYSPDHKCSVFYAAPTKSKLLSTLCSADVCQCAEGKCPRQRRSLERGVE 1600
1601 DKDGYRMKFACYYPRVEYGFQVKVLREDSRAAFRLFETKITQVLHFTKDA 1650
1651 KASIGQTRNFLVRASCRLRLEPSKEYLIMGMDGVTSDLKGDPQYLLDSNT 1700
1701 WIEEMPSERLCRSTRQRAACGQLNDFLQEYSSQGCQV 1737
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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