 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8BLA8 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MKRGLRRILLPEERKEVQGVVYRGVGEDMDCSKESFKVDIEGDMCRLEDF 50
51 IKNRRKLSKYEDENLCPLHHAAAEGQVELMELIINGSSCEVLNIMDGYGN 100
101 TPLHCAAEKNQVESVKFLLSQGANPNLRNRNMMSPLHIAVHGMYNEVIKV 150
151 LTEHKATNINLEGENGNTALMSTCAKDNSEALQILLEKGAKLCKSNKWGD 200
201 YPVHQAAFSGAKKCMELILAYGEKNGYSRETHINFVNHKKASPLHLAVQS 250
251 GDLDMIKMCLDNGAHIDMMENAKCMALHFAATQGATDIVKLMISSYTGSS 300
301 DIVNAVDGNQETLLHRASLFDHHDLAEYLISVGADINSTDSEGRSPLILA 350
351 TASASWNIVNLLLCKGAKVDIKDHLGRNFLHLTVQQPYGLRNLRPEFMQM 400
401 QHIKELVMDEDNDGCTPLHYACRQGVPVSVNNLLGFNVSIHSKSKDKKSP 450
451 LHFAASYGRINTCQRLLQDISDTRLLNEGDLHGMTPLHLAAKNGHDKVVQ 500
501 LLLKKGALFLSDHNGWTALHHASMGGYTQTMKVILDTNLKCTDRLDEEGN 550
551 TALHFAAREGHAKAVAMLLSYNADILLNKKQASFLHIALHNKRKEVVLTT 600
601 IRNKRWDECLQVFTHNSPSNRCPIMEMVEYLPECMKVLLDFCMIPSTEDK 650
651 SCQDYHIEYNFKYLQCPLSMTKKVAPTQDVVYEPLTILNVMVQHNRIELL 700
701 NHPVCREYLLMKWCAYGFRAHMMNLGSYCLGLIPMTLLVVKIQPGMAFNS 750
751 TGIINGTSSTHEERIDTLNSFPIKICMILVFLSSIFGYCKEVIQIFQQKR 800
801 NYFLDYNNALEWVIYTTSIIFVLPLFLNIPAYMQWQCGAIAIFFYWMNFL 850
851 LYLQRFENCGIFIVMLEVIFKTLLRSTGVFIFLLLAFGLSFYVLLNFQDA 900
901 FSTPLLSLIQTFSMMLGDINYRDAFLEPLFRNELAYPVLTFGQLIAFTMF 950
951 VPIVLMNLLIGLAVGDIAEVQKHASLKRIAMQVELHTNLEKKLPLWYLRK 1000
1001 VDQRSTIVYPNRPRHGRMLRFFHYFLNMQETRQEVPNIDTCLEMEILKQK 1050
1051 YRLKDLTSLLEKQHELIKLIIQKMEIISETEDEDNHCSFQDRFKKERLEQ 1100
1101 MHSKWNFVLNAVKTKTHCSISHPDF 1125
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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