 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q63374 from www.uniprot.org...
The NucPred score for your sequence is 0.35 (see score help below)
1 MALGSRWRPPPQLPPLLLLLALVAGVRGLEFGGGPGQWARYARWAGAAST 50
51 GELSFSLRTNATRALLLYLDDGGDCDFLELLLVDGRLRLRFTLSCAEPAT 100
101 LQLDTPVADDRWHMVLLTRDARRTALAVDGEARAAEVRSKRREMQVASDL 150
151 FVGGIPPDVRLSALTLSTVKYEPPFRGLLANLKLGERPPALLGSQGLRGA 200
201 AADPLCAPARNPCANGGLCTVLAPGEVGCDCSHTGFGGKFCSEGEHPMEG 250
251 PAHLTLNSPVGSLLFSEGGAGRGGAGDVHQPTKGKEEFVATFKGNEFFCY 300
301 DLSHNPIQSSTDEITLAFRTLQRNGLMLHTGKSADYVNLSLKSGAVWLVI 350
351 NLGSGAFEALVEPVNGKFNDNAWHDVRVTRNLRQHAGIGHAMVNKLHYLV 400
401 TISVDGILTTTGYTQEDYTMLGSDDFFYIGGSPNTADLPGSPVSNNFMGC 450
451 LKDVVYKNNDFKLELSRLAKEGDPKMKLQGDLSFRCEDVAALDPVTFESP 500
501 EAFVALPRWSAKRTGSISLDFRTTEPNGLLLFSQGRRAGAGVGSHSSSQR 550
551 ADYFAMELLDGYLYLLLDMGSGGIKLRASSRKVNDGEWCHVDFQRDGRKG 600
601 SISVNSRSTPFLATGESEVLDLESELYLGGLPEGGRVDLPLPPEVWTAAL 650
651 RAGYVGCVRDLFIDGRSRDLRGLAEAQGAVGVAPFCSRETLKQCASAPCR 700
701 NGGICREGWNRFVCDCIGTGFLGRVCEREATVLSYDGSMYMKIMLPNAMH 750
751 TEAEDVSLRFMSQRAYGLMMATTSRESADTLRLELDGGQMKLTVNLDCLR 800
801 VGCAPSAAGKGPETLFAGHKLNDNEWHTVRVVRRGKSLQLSVDNVTVEGQ 850
851 MAGAHTRLEFHNIETGIMTERRFISVVPSNFIGHLSGLVFNGQPYMDQCK 900
901 DGDITYCELNARFGLRAIVADPVTFKSRSSYLALATLQAYASMHLFFQFK 950
951 TTAPDGLLLFNSGNGNDFIVIELVKGYIHYVFDLGNGPSLMKGNSDKPVN 1000
1001 DNQWHNVVVSRDPGNVHTLKIDSRTVTQHSNGARNLDLKGELYIGGLSKN 1050
1051 MFSNLPKLVASRDGFQGCLASVDLNGRLPDLIADALHRIGQVERGCDGPS 1100
1101 TTCTEESCANQGVCLQQWDGFTCDCTMTSYGGPVCNDPGTTYIFGKGGAL 1150
1151 ITYTWPPNDRPSTRMDRLAVGFSTHQRSAVLVRVDSASGLGDYLQLHIDQ 1200
1201 GTVGVIFNVGTDDITIDEPNAIVSDGKYHVVRFTRSGGNATLQVDSWPVN 1250
1251 ERYPAGNFDNERLAIARQRIPYRLGRVVDEWLLDKGRQLTIFNSQAAIKI 1300
1301 GGRDQGRPFQGQVSGLYYNGLKVLALAAESDPNVRTEGHLRLVGEGPSVL 1350
1351 LSAETTATTLLADMATTIMETTTTMATTTTRRGRSPTMRDSTTQNTDDLL 1400
1401 VASAECPSDDEDLEECEPSTGGELILPIITEDSLDPPPVATRSPFVPPPP 1450
1451 TFYPFLTGVGATQDTLPPPAARRPSSGGPCQAERDDSDCEEPVEASGFAS 1500
1501 GEVFDSSLPPTDDEDFYTTFPLVTDRTTLLSPRKPAPRPNLRTDGATGAP 1550
1551 GVLLAPSAPAPNLPAGKMNHRDPLQPLLENPPLGPGVPTAFEPRRPPPLR 1600
1601 PGVTSVPGFPRLPTANPTGPGERGPPGAVEVIRESSSTTGMVVGIVAAAA 1650
1651 LCILILLYAMYKYRNRDEGSYQVDQSRNYISNSAQSNGAVVKEKAPAAPK 1700
1701 TPSKAKKNKDKEYYV 1715
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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