 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O88904 from www.uniprot.org...
The NucPred score for your sequence is 0.87 (see score help below)
1 MASQLQVFSPPSVSSSAFCSAKKLKIEPSGWDVSGQSSNDKYYTHSKTLP 50
51 ATQGQASSSHQVANFNLPAYDQGLLLPAPAVEHIVVTAADSSGSAATATF 100
101 QSSQTLTHRSNVSLLEPYQKCGLKRKSEEVESNGSVQIIEEHPPLMLQNR 150
151 TVVGAAATTTTVTTKSSSSSGEGDYQLVQHEILCSMTNSYEVLEFLGRGT 200
201 FGQVAKCWKRSTKEIVAIKILKNHPSYARQGQIEVSILSRLSSENADEYN 250
251 FVRSYECFQHKNHTCLVFEMLEQNLYDFLKQNKFSPLPLKYIRPILQQVA 300
301 TALMKLKSLGLIHADLKPENIMLVDPVRQPYRVKVIDFGSASHVSKAVCS 350
351 TYLQSRYYRAPEIILGLPFCEAIDMWSLGCVIAELFLGWPLYPGASEYDQ 400
401 IRYISQTQGLPAEYLLSAGTKTTRFFNRDPNLGYPLWRLKTPEEHELETG 450
451 IKSKEARKYIFNCLDDMAQVNMSTDLEGTDMLAEKADRREYIDLLKKMLT 500
501 IDADKRITPLKTLNHQFVTMSHLLDFPHSSHVKSCFQNMEICKRRVHMYD 550
551 TVSQIKSPFTTHVAPNTSTNLTMSFSNQLNTVHNQASVLASSSTAAAATL 600
601 SLANSDVSLLNYQSALYPSSAAPVPGVAQQGVSLQPGTTQICTQTDPFQQ 650
651 TFIVCPPAFQTGLQATTKHSGFPVRMDNAVPIVPQAPAAQPLQIQSGVLT 700
701 QGSCTPLMVATLHPQVATITPQYAVPFTLSCAAGRPALVEQTAAVLQAWP 750
751 GGTQQILLPSAWQQLPGVALHNSVQPAAVIPEAMGSSQQLADWRNAHSHG 800
801 NQYSTIMQQPSLLTNHVTLATAQPLNVGVAHVVRQQQSSSLPSKKNKQSA 850
851 PVSSKSSLEVLPSQVYSLVGSSPLRTTSSYNSLVPVQDQHQPIIIPDTPS 900
901 PPVSVITIRSDTDEEEDNKYKPNSSSLKARSNVISYVTVNDSPDSDSSLS 950
951 SPHPTDTLSALRGNSGTLLEGPGRPAADGIGTRTIIVPPLKTQLGDCTVA 1000
1001 TQASGLLSSKTKPVASVSGQSSGCCITPTGYRAQRGGASAVQPLNLSQNQ 1050
1051 QSSSASTSQERSSNPAPRRQQAFVAPLSQAPYAFQHGSPLHSTGHPHLAP 1100
1101 APAHLPSQPHLYTYAAPTSAAALGSTSSIAHLFSPQGSSRHAAAYTTHPS 1150
1151 TLVHQVPVSVGPSLLTSASVAPAQYQHQFATQSYIGSSRGSTIYTGYPLS 1200
1201 PTKISQYSYL 1210
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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