 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UKK3 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MVMGIFANCIFCLKVKYLPQQQKKKLQTDIKENGGKFSFSLNPQCTHIIL 50
51 DNADVLSQYQLNSIQKNHVHIANPDFIWKSIREKRLLDVKNYDPYKPLDI 100
101 TPPPDQKASSSEVKTEGLCPDSATEEEDTVELTEFGMQNVEIPHLPQDFE 150
151 VAKYNTLEKVGMEGGQEAVVVELQCSRDSRDCPFLISSHFLLDDGMETRR 200
201 QFAIKKTSEDASEYFENYIEELKKQGFLLREHFTPEATQLASEQLQALLL 250
251 EEVMNSSTLSQEVSDLVEMIWAEALGHLEHMLLKPVNRISLNDVSKAEGI 300
301 LLLVKAALKNGETAEQLQKMMTEFYRLIPHKGTMPKEVNLGLLAKKADLC 350
351 QLIRDMVNVCETNLSKPNPPSLAKYRALRCKIEHVEQNTEEFLRVRKEVL 400
401 QNHHSKSPVDVLQIFRVGRVNETTEFLSKLGNVRPLLHGSPVQNIVGILC 450
451 RGLLLPKVVEDRGVQRTDVGNLGSGIYFSDSLSTSIKYSHPGETDGTRLL 500
501 LICDVALGKCMDLHEKDFSLTEAPPGYDSVHGVSQTASVTTDFEDDEFVV 550
551 YKTNQVKMKYIIKFSMPGDQIKDFHPSDHTELEEYRPEFSNFSKVEDYQL 600
601 PDAKTSSSTKAGLQDASGNLVPLEDVHIKGRIIDTVAQVIVFQTYTNKSH 650
651 VPIEAKYIFPLDDKAAVCGFEAFINGKHIVGEIKEKEEAQQEYLEAVTQG 700
701 HGAYLMSQDAPDVFTVSVGNLPPKAKVLIKITYITELSILGTVGVFFMPA 750
751 TVAPWQQDKALNENLQDTVEKICIKEIGTKQSFSLTMSIEMPYVIEFIFS 800
801 DTHELKQKRTDCKAVISTMEGSSLDSSGFSLHIGLSAAYLPRMWVEKHPE 850
851 KESEACMLVFQPDLDVDLPDLASESEVIICLDCSSSMEGVTFLQAKQIAL 900
901 HALSLVGEKQKVNIIQFGTGYKELFSYPKHITSNTMAAEFIMSATPTMGN 950
951 TDFWKTLRYLSLLYPARGSRNILLVSDGHLQDESLTLQLVKRSRPHTRLF 1000
1001 ACGIGSTANRHVLRILSQCGAGVFEYFNAKSKHSWRKQIEDQMTRLCSPS 1050
1051 CHSVSVKWQQLNPDVPEALQAPAQVPSLFLNDRLLVYGFIPHCTQATLCA 1100
1101 LIQEKEFRTMVSTTELQKTTGTMIHKLAARALIRDYEDGILHENETSHEM 1150
1151 KKQTLKSLIIKLSKENSLITQFTSFVAVEKRDENESPFPDIPKVSELIAK 1200
1201 EDVDFLPYMSWQGEPQEAVRNQSLLASSEWPELRLSKRKHRKIPFSKRKM 1250
1251 ELSQPEVSEDFEEDGLGVLPAFTSNLERGGVEKLLDLSWTESCKPTATEP 1300
1301 LFKKVSPWETSTSSFFPILAPAVGSYLPPTARAHSPASLSFASYRQVASF 1350
1351 GSAAPPRQFDASQFSQGPVPGTCADWIPQSASCPTGPPQNPPSSPYCGIV 1400
1401 FSGSSLSSAQSAPLQHPGGFTTRPSAGTFPELDSPQLHFSLPTDPDPIRG 1450
1451 FGSYHPSASSPFHFQPSAASLTANLRLPMASALPEALCSQSRTTPVDLCL 1500
1501 LEESVGSLEGSRCPVFAFQSSDTESDELSEVLQDSCFLQIKCDTKDDSIL 1550
1551 CFLEVKEEDEIVCIQHWQDAVPWTELLSLQTEDGFWKLTPELGLILNLNT 1600
1601 NGLHSFLKQKGIQSLGVKGRECLLDLIATMLVLQFIRTRLEKEGIVFKSL 1650
1651 MKMDDASISRNIPWAFEAIKQASEWVRRTEGQYPSICPRLELGNDWDSAT 1700
1701 KQLLGLQPISTVSPLHRVLHYSQG 1724
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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