 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5T5C0 from www.uniprot.org...
The NucPred score for your sequence is 0.77 (see score help below)
1 MRKFNIRKVLDGLTAGSSSASQQQQQQHPPGNREPEIQETLQSEHFQLCK 50
51 TVRHGFPYQPSALAFDPVQKILAVGTQTGALRLFGRPGVECYCQHDSGAA 100
101 VIQLQFLINEGALVSALADDTLHLWNLRQKRPAILHSLKFCRERVTFCHL 150
151 PFQSKWLYVGTERGNIHIVNVESFTLSGYVIMWNKAIELSSKSHPGPVVH 200
201 ISDNPMDEGKLLIGFESGTVVLWDLKSKKADYRYTYDEAIHSVAWHHEGK 250
251 QFICSHSDGTLTIWNVRSPAKPVQTITPHGKQLKDGKKPEPCKPILKVEF 300
301 KTTRSGEPFIILSGGLSYDTVGRRPCLTVMHGKSTAVLEMDYSIVDFLTL 350
351 CETPYPNDFQEPYAVVVLLEKDLVLIDLAQNGYPIFENPYPLSIHESPVT 400
401 CCEYFADCPVDLIPALYSVGARQKRQGYSKKEWPINGGNWGLGAQSYPEI 450
451 IITGHADGSVKFWDASAITLQVLYKLKTSKVFEKSRNKDDRPNTDIVDED 500
501 PYAIQIISWCPESRMLCIAGVSAHVIIYRFSKQEVITEVIPMLEVRLLYE 550
551 INDVETPEGEQPPPLPTPVGGSNPQPIPPQSHPSTSSSSSDGLRDNVPCL 600
601 KVKNSPLKQSPGYQTELVIQLVWVGGEPPQQITSLAVNSSYGLVVFGNCN 650
651 GIAMVDYLQKAVLLNLGTIELYGSNDPYRREPRSPRKSRQPSGAGLCDIS 700
701 EGTVVPEDRCKSPTSGSSSPHNSDDEQKMNNFIEKVKTKSRKFSKMVAND 750
751 IAKMSRKLSLPTDLKPDLDVKDNSFSRSRSSSVTSIDKESREAISALHFC 800
801 ETFTRKTDSSPSPCLWVGTTLGTVLVIALNLPPGGEQRLLQPVIVSPSGT 850
851 ILRLKGAILRMAFLDTTGCLIPPAYEPWREHNVPEEKDEKEKLKKRRPVS 900
901 VSPSSSQEISENQYAVICSEKQAKVISLPTQNCAYKQNITETSFVLRGDI 950
951 VALSNSICLACFCANGHIMTFSLPSLRPLLDVYYLPLTNMRIARTFCFTN 1000
1001 NGQALYLVSPTEIQRLTYSQETCENLQEMLGELFTPVETPEAPNRGFFKG 1050
1051 LFGGGAQSLDREELFGESSSGKASRSLAQHIPGPGGIEGVKGAASGVVGE 1100
1101 LARARLALDERGQKLGDLEERTAAMLSSAESFSKHAHEIMLKYKDKKWYQ 1150
1151 F 1151
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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