 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q925T6 from www.uniprot.org...
The NucPred score for your sequence is 0.63 (see score help below)
1 MIAVSFKCRCQILRRLTKDESPYTKSASQTKPPDGALAVRRQSIPEEFKG 50
51 STVVELMKKEGTTLGLTVSGGIDKDGKPRVSNLRQGGIAARSDQLDVGDY 100
101 IKAVNGINLAKFRHDEIISLLKNVGERVVLEVEYELPPVSVQGSSVMFRT 150
151 VEVTLHKEGNTFGFVIRGGAHDDRNKSRPVVITCVRPGGPADREGTIKPG 200
201 DRLLSVDGIRLLGTTHAEAMSILKQCGQEATLLIEYDVSVMDSVATASGP 250
251 LLVEVAKTPGASLGVALTTSVCCNKQVIVIDKIKSASIADRCGALHVGDH 300
301 ILSIDGTSMEYCTLAEATQFLANTTDQVKLEILPHHQTRLALKGPDHVKI 350
351 QRSDRQHPWDAWASNQCGVHTNHHHNTYHPDHCRVPALTFPKALPPNSPP 400
401 AMVPSSSPTSMSAYSLSSLNMGTLPRSLYSTSPRGTMMRRRLKKKDFKSS 450
451 LSLASSTVGLAGQVVHTETTEVVLTADPVTGFGIQLQGSVFATETLSSPP 500
501 LISYIEADSPAERCGVLQIGDRVMAINGIPTEDSTFEEANQLLRDSSITS 550
551 KVTLEIEFDVAESVIPSSGTFHVKLPKKHSVELGITISSPSSRKPGDPLV 600
601 ISDIKKGSVAHRTGTLELGDKLLAIDNIRLDNCSMEDAVQILQQCEDLVK 650
651 LKIRKDEDNSDEQESSGAIIYTVELKRYGGPLGITISGTEEPFDPIIISS 700
701 LTKGGLAERTGAIHIGDRILAINSSSLKGKPLSEAIHLLQMAGETVTLKI 750
751 KKQTDAQSASSPKKFPIPGHSGDLGDGEEDPSPIQKPGKLSDAYPSTVPS 800
801 VDSAVDSWDGSGIDASYGSQGSTFQTSGYNYNTYDWRSPKQRTSLSPVPK 850
851 PRSQTYPDVGLSNEDWDRSTASGFVGASDSADAEQEENFWSQALEDLETC 900
901 GQSGILRELEEKADRRVSLRNMTLLATIMSGSTMSLNHEAPMARSQLGRQ 950
951 ASFQERSSSRPHYSQTTRSNTLPSDVGRKSVTLRKMKQEIKEIMSPTPVE 1000
1001 LHKVTLYKDSGMEDFGFSVADGLLEKGVYVKNIRPAGPGDVGGLKPYDRL 1050
1051 LQVNHVRTRDFDCCLVVPLIAESGNKLDLVISRNPLASQKSIEQPALPSD 1100
1101 WSEQNSAFFQQPSHGGNLETREPTNTL 1127
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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