| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q11102 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MSRSPRPHGTHEPAVGVTRPFVRQSHPEIAAWPAPPPAHQLGCLSGNVRT 50
51 PVGGPAPPSPVLRRAPSGPISPSPISPVSQHSRASSRHDIDNTSLLSILK 100
101 LSHVARESSRNTSRNNSPQPAGRETELKRKIQTLEETVAEYERQKYNVMG 150
151 TFSEYRERVAERERKLEAEYSGKIIALSEEVLGAKKDFEARMKSFQALQD 200
201 KFEREKEQALEKLRKEHQKEIQVLEQRFSDTQLLNLEQKYIIEIQRLEEE 250
251 RKSLRTEKERLGETFEMKLRRAQSLYETELTAAKMLYTKELEALRDHEEA 300
301 LKEELLARQDEFHDRLQELQLQSKRSREDLVSCKNDVTALEKKLHNKEKE 350
351 VQTLTKELDQVKTETNDKIRRLTEVTSEFAEYRKKFQQQEEELRRKARLL 400
401 TVVEAAKEKLESVISDLQVEVKALKNKVEFLEKERENLQSQSESQTQLQS 450
451 SQVDALEAVLHSVTKEKETTKEHYEGLLLKERQQAESREHAMKKEFSCKL 500
501 NELEEQYTSLKEELEESARLDKDELREASEIEIQALRTEKSILAAEIRVL 550
551 TQKIEDEEQDDITEQLAKIVEDTSQLTRTLEEYRERITGKDAEILNLRKQ 600
601 LEKEISHTEDRNRLLHENTQKELEAHKETHTETVRVLEAEIDQFKSAFEN 650
651 EQEYGKEKSAKIRELEAQNKTLLSEMEKVKHVAENLEAFTSDKDNLLEEL 700
701 ESKNKNIEHLKQEIAQLNEKISTKETEKDSELEKTIAQLEIDNSSKSDQI 750
751 EKLHLRVNDMLDQMGTIKDELVKKNEEIKTISAKTAQLLESNTVESETKL 800
801 ASVTEEREKEIQSFQTQISEKDNEVLTKAERINELETCLKEREVELTGMR 850
851 TKLDDMTQQLNEETTVVLFDNSIQEKIDEKEATINEMNERLKSRENEIAK 900
901 LHEEMYMQKTQNEKRNEEQSKLFQELMFEKEQLEAEKAEQSHIEAEVEQV 950
951 FQADKESKWKEQIEDLENALQRKNELIQQLQDRQTDESTSEPHTKKRMSI 1000
1001 TSHGVFQNFVSQMKDKREEASEKRTRKEAEKKAEKEKEKAEKAAKEAAKE 1050
1051 LAREKSPARAKSPSILTRLRDRSPAKSKSDNLESTPSSSSRNLLSPFDAE 1100
1101 KRMERSSPSQQLFSRTKKDSSSEKRPAWKF 1130
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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