| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9I920 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MEEARAATNGGSGESQKLSNGEKSSQLEPGDVGNELLADIELEEDDYLDV 50
51 VPPSPEEELPSFSPSVRNVSNIFKESPTDGRSAVHGTESEPELMAPKQPA 100
101 AEQDSSAEHADKGLHLEQQLYSVMEDICKLVDAIPLHELTSISCAKELLQ 150
151 QRELRRKLLADSGALNTNSVNGPRNWKACVQQDPSSRPGTPLCSGPGRGV 200
201 SSVGSTPKSTNLPSVLSRTVNSSSFSTIRNQTLDKLDTSYSSKETDQEVI 250
251 CLEPAALPSPKVNGKGSTSLSRPSEASFNGSWCEKPTGRDSGNWRVPERP 300
301 TASTALKAQHTAPAGNPASGCWDVNDTDFDLDHFDIDDFDEGWEEAVAPE 350
351 AAPEAPPAPQWQPLREGSASLRCRLLAAAAGSAPGPHPTAPKSGCGISAK 400
401 SSSEPLVHNPAHERFRGMKFSHSEEMLKIFHRKFGLHSFRTNQLEAINAA 450
451 LLGEDCFILMPTGGGKSLCYQLPACVSAGVTVVISPLRSLIIDQVQKLKT 500
501 LDIASTYLTGDITDADASKTYMQLSKKDPIIKLLYVTPEKVCASNRLLSA 550
551 LENLYNRKLLARFVIDEAHCVSQWGHDFRKDYKRLNMLRKKFHSVPMMAL 600
601 TATANPRVQKDIQNQLEMLKPQVFTMSFNRHNLKYDVLPKKPKKVAMDCL 650
651 EWIKKYHPHDSGIIYCLSRHECDTTAAILQKEGLAALAYHAGLTDSNRDL 700
701 VQKKWVNQEGCQVICATIAFGMGIDKPDVRYVIHASLPKSIEGYYQESGR 750
751 AGRDGEMSHCLLFYSYSDVTRLRRLILMEKDGNSHTRQTHFNNLYSMVHY 800
801 CENVVDCRRIQLLAYFGETDFNPNFCKDHPEVICDNCSRKKDYKSRNVTD 850
851 EVKSIIRFVQQHCGQVGGINGNRNTGSGRYTLNMMVDIFLGAKSAKIQSG 900
901 IFGKGAAYSRHNVERLFRKLVLDKILDEDLYITANDQAVAYVVLGEKAQA 950
951 VLNGLLQVEFHETENASAIRKQRASVTKMSQREEMVKKCLGELTDTCKTL 1000
1001 GKIFDVHYFNIFSTSTLKKIAETLSSDAEVLLQIDGVTEDKLEKYGAEII 1050
1051 KVMDKYSEWTTPEDAACQSVDTAPGSAGTPGSEEEAADDVVTSSYFGGNA 1100
1101 NQRRKRKRLPNSGESKRKKTSSGGSQQFYSKGARYRRARRAPGSRAAAPA 1150
1151 QSSALRGAGARLGIMAPPKPSSRHFLQPSYAVL 1183
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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