 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2KN95 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MKKSVRPAASKVSGERGKPEVAGNAAAGKPASKSSTAAPLSKVKSSDDLL 50
51 AAMAGGNPASCNAVSKSKRTTSVGTTASTLDSKPKTASGTTSKRLASSLS 100
101 KETNLTRDRLRTSRASANKKQSAAGPVGGDAASGKRSRGQTLAESEGRMS 150
151 KSKSDGQISDKVALETKVKDLLGLAKSKDVEILHLRSELRDMRAQLGLGG 200
201 EEPQEGAVEEEKPHVSAITAADVESTLILLQEQNQAIREELNLLKSENRM 250
251 LKDRLNALGFSLEQRLDGSDKLFSYASLSPDLAAGSGQSDGGGTGTLASS 300
301 VEGSAPGSLEDLLTGHQHGGSADNLDSESSEVYQAVTSSDDALDAPSGAS 350
351 SSSESECAPSRERSRRGSSGNASEVSVACLTERIHQMEENQHSTAEELQA 400
401 TLQELADLQQITQELNGENERLGEEKVILMDSLCQQSDKLELYGRQIEYL 450
451 RSLLDEHHVSYVLEEDIKSGRYMELEQRYADLAENGRFEREQLLGVQQHL 500
501 SNTLKMAEQDNAEAQEMIGALKERNHQMERIMESERQGRAAVEATLEEYK 550
551 EVASSDQAELSRCRAQLEQERQRVAELYSLHTAGDKNDICQLLEGVRLGK 600
601 EEAEAKAAKLQEGLEQAHGELSHLRETFSKLDREYREFQEQAQQQMGEQE 650
651 RALEKQRLDLQEKETEVADMKETIFELEDEVEQHRALKLHDNLIITDLEN 700
701 SVKKLQDQKHDMEREIKILHRRLREESMEWRQFQADLQTAVVIANDIKSE 750
751 AQEEIGDLRRRLQEAQEKNEKLSKELEEVKSRKQDEERGRVYNYMNAVER 800
801 DLAALRQGMGLSRRSSTSSEPSPTVKTLIKSFDSASQGPPSSGASVTPTA 850
851 SAAPLPRTPLSPSPMKTPPAAAVSPIQRHSVSGSMSAAKPLSSLGDKRPT 900
901 YPDISLPAEHLLRGSAAGRPPSALQRVSNMDSTKAISVSRRSSEEMKRDM 950
951 AAPDGASSASLMAMSAASSPLALASSSPTASVTPTTRSRLREERKDPLSA 1000
1001 LAREYGGSKRNALLKWCQKKTEGYQNIDITNFSSSWNDGLAFCAVLHTYL 1050
1051 PAHIPYQELTSQEKRRNFTLAFQAAESVGIKCTLDINEMVHTERPDWQSV 1100
1101 MTYVTAIYKYFET 1113
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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