 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9HE02 from www.uniprot.org...
The NucPred score for your sequence is 0.63 (see score help below)
1 MSYQVCFKKYVKMRQWPHVLSLRVYASYFLLYNNLPLSSAMVHDGVHLIS 50
51 IKTILTDQPCPNTIYYAKYQVQRKDNEDAASLLEDKEAYLRNQDCIVHAK 100
101 NDLLFVYDFQAIPSIPEESSSFMLLNSGAFSRLALFQKDELALLLDLYIN 150
151 FLQGLKKTVLYWLCKEYNFVPIYGVLLPLKLHPSFDTQLWNIYGYPVVDL 200
201 QLSVLSKGHIEFYLKPTRQTVYRLSEVDNLVKKLDTVIRLAPTGCLATLT 250
251 SVHANASAQTVDALKHRYGFSLTTTSKWVGVTLESSALEFSWPLELCFLE 300
301 TSALRMNDDSLSSNLTDLNNLVLPSNVVNNKKELTEFANEEAEASDKRKE 350
351 GFTEKEETADAVVTLVPSHSSSPVNYSINSAKSTPASIKVNEEILVADHN 400
401 VSDDILMEEIDDVGITEADFDYFDLPNVEEKVEMIEPNFANTMTTLDNEE 450
451 INTSISQSNTSPNLNTHENIPKQMEIQSDDRMVTEDLNPYNVEVDIPEIS 500
501 LNISDSKIPTSAYMPSYYSAVIFPSSISSIFQKYNYGGKYWCPSPSLSTE 550
551 DLFESFSVAESVTSTDEDICSTNFIQQDFTMEYNHDFFSSSKTPTNISEQ 600
601 SNPDSNYDTLSLAHQVLMNESKSANFDFSFLKSLDLQPTITLGKNDLLNA 650
651 ILSQNLWFRSLPFWKSMTTSFMMSQDVLNFSSYMRKPIRDYLEKILLGES 700
701 SAVFLSKSPENYLSSINNGHHALNDNPPSQVNFSETLVNFSQPPRVLLKY 750
751 NEKKLSLDSSAPENWISLCLQPYGESKDFEVFLLSSKSPDVSSKAISFFY 800
801 DVQLAYENCKLGKLNLSETSINERVMGFSTNINETDNYDDNETTQSDTAT 850
851 SYEQLASVCVNELSGKNVLFFYFLEDDSEKLLKACQHFICVKDSIKRLGD 900
901 NKFEDKSLRICTIPNSIFDSPNSHTTNSNSFFTKVSLDIYNNDPLLMDGS 950
951 LKRREPAFLLKKPLLSTLNYQLKDINPRSSALGEYALHVTYTTVEEHLLI 1000
1001 CNWNDSYGEFETERRYFLQDLEIEDALQQILEVTFTFLNSMHMDWIVIVM 1050
1051 KIGEMSDAEYLFWDQAIIPENLQGNVSLTVGYCSAEHGPGSTSKVFSRIP 1100
1101 YSASSTVIRNNSSHELSLVAFIREMAMPVPNDEFKKISTILARGYLALDE 1150
1151 DESYLPLLSIHLLISRNHDPYLMLNLILKHYLSMIYLQFRTYVSFSSLPL 1200
1201 HISTVLYQKQLLQFMASDITHPVTS 1225
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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