| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q76FK4 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MKVNRETKRLYVGGLSQDISEADLQNQFSRFGEVSDVEIITRKDDQGNPQ 50
51 KVFAYINISVAEADLKKCMSVLNKTKWKGGTLQIQLAKESFLHRLAQERE 100
101 AAKAKKEESTTGNANLLEKTGGVDFHMKAVPGTEVPGHKNWVVSKFGRVL 150
151 PVLHLKNQHKRKIIKYDPSKYCHNLKKIGEDFSNTIPISSLTWELEGGND 200
201 PMSKKRRGEFSDFHGPPKKIIKVQKDESSTGSLAMSTRPRRVIERPPLTQ 250
251 QQAAQKRTCDSITPSKSSPVPVSDTQKLKNLPFKTSGLETAKKRNSISDD 300
301 DTDSEDELRMMIAKEENLQRTTQPSINESESDPFEVVRDDFKSGVHKLHS 350
351 LIGLGIKNRVSCHDSDDDIMRNDREYDSGDTDEIIAMKKNVAKVKNSTEF 400
401 SQMEKSTKKTSFKNRENCELSDHCIKLQKRKSNVESALSHGLKSLNRKSP 450
451 SHSSSSEDADSASELADSEGGEEYNAMMKNCLRVNLTLADLEQLAGSDLK 500
501 VPNEDTKSDGPETTTQCKFDRGSKSPKTPTGLRRGRQCIRPAEIVASLLE 550
551 GEENTCGKQKPKENNLKPKFQAFKGVGCLYEKESMKKSLKDSVASNNKDQ 600
601 NSMKHEDPSIISMEDGSPYVNGSLGEVTPCQHAKKANGPNYIQPQKRQTT 650
651 FESQDRKAVSPSSSEKRSKNPISRPLEGKKSLSLSAKTHNIGFDKDSCHS 700
701 TTKTEASQEERSDSSGLTSLKKSPKVSSKDTREIKTDFSLSISNSSDVSA 750
751 KDKHAEDNEKRLAALEARQKAKEVQKKLVHNALANLDGHPEDKPTHIIFG 800
801 SDSECETEETSTQEQSHPGEEWVKESMGKTSGKLFDSSDDDESDSEDDSN 850
851 RFKIKPQFEGRAGQKLMDLQSHFGTDDRFRMDSRFLETDSEEEQEEVNEK 900
901 KTAEEEELAEEKKKALNVVQSVLQINLSNSTNRGSVAAKKFKDIIHYDPT 950
951 KQDHATYERKRDDKPKESKAKRKKKREEAEKLPEVSKEMYYNIAMDLKEI 1000
1001 FQTTKYTSEKEEGTPWNEDCGKEKPEEIQDPAALTSDAEQPSGFTFSFFD 1050
1051 SDTKDIKEETYRVETVKPGKIVWQEDPRLQDSSSEEEDVTEETDHRNSSP 1100
1101 GEASLLEKETTRFFFFSKNDERLQGSDLFWRGVGSNMSRNSWEARTTNLR 1150
1151 MDCRKKHKDAKRKMKPK 1167
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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