 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6ZPY7 from www.uniprot.org...
The NucPred score for your sequence is 0.76 (see score help below)
1 MADAAASPVGKRLLLLFADPTASASASAPTAAAVVSGDPGPALRTRAWRA 50
51 GTVRAMSGAVPQDLAIFVEFDGCNWKQHSWVKVHAEDVLALLLEGSLVWA 100
101 PRKDPVLLQGTRVPVAQWPALTFTPLVDKLGLGSVVPVEYLVDRELRFLS 150
151 DANGMHLFQMGTDVQNQILLEHAALRETVNALISDQKLQEIFSRGPYSVQ 200
201 GHRVKVYQPEGEEVWLCGVVSRQDSVTRLMEVSITETGEVKSVDPRLTHV 250
251 MLMDSSTPQSEGGTIKAVKSSKGKKKRESIEGRDGRRRKSASDSGCDPAT 300
301 KKLKGDRGEVDSNGSDGGEASRGPWKGGNASGEPGLEQRAKQPPSTFVPQ 350
351 INRNIRFATYTKENGRTLVVQDEPVGGDTPVPFTPYASATGQTPLAPEVG 400
401 GAENKEAGKTLEQVSQGMVASAAVVTTASSTPTTVRISDTGLASGTGPEK 450
451 QKGSWSQASGENSRNSSLASSGFGVSLSSLSQPLTFGSGRSQSNGVLATD 500
501 NKPLGFSFSCSSASESQKDSDLSKNLFFQCMSQNVPSTNYLSRVSESVAD 550
551 DSSSRDSFTQSLESLTSGLCKGRSVLGADTQPGPKAGSSVDRKVPAESMP 600
601 TLTPAFPRSLLNTRTPENHENLFLQPPKLSREEPSNPFLAFVEKVEHSPF 650
651 SSFVSQASGSSSSATSVTSKATASWPESHSSAESAPLAKKKPLFITTDSS 700
701 KLVSGVLGSALSTGSPSLSAVGNGRSSSPTNSLTQPIEMPTLSSSPTEER 750
751 PTVGPGQQDNPLLKTFSTVFGRHSGSFLSAPAEFAQENKAPFEAVKRFSL 800
801 DERSLACRQDSDSSTNSDLSDLSDSEEQLQAKSGLKGIPEHLMGKLGPNG 850
851 ERSAELLLGKGKGKQAPKGRPRTAPLKVGQSVLKDVSKVRKLKQSGEPFL 900
901 QDGSCINVAPHLHKCRECRLERYRKFKEQEQDDSTVACRFFHFRRLVFTR 950
951 KGVLRVEGFLSPQQSDPDAMNLWIPSSSLAEGIDLETSKYILANVGDQFC 1000
1001 QLVMSEKEAMMMVEPHQKVAWKRAVRGVREMCDVCETTLFNIHWVCRKCG 1050
1051 FGVCLDCYRLRKSRPRSETEEMGDEEVFSWLKCAKGQSHEPENLMPTQII 1100
1101 PGTALYNIGDMVHAARGKWGIKANCPCISRQSKSVLRPAVTNGISQLPSV 1150
1151 TPSASSGNETTFSSGGGAAAVTNPEPDQVPKGAGTDGRSEEPLKAEGSAS 1200
1201 NSNSELKAIRPPCPDTAPPSSALHWLADLATQKAKEETKDAGSLRSVLNK 1250
1251 ESHSPFGLDSFNSTAKVSPLTPKLFNSLLLGPTASNSKTEGSSLRDLLHS 1300
1301 GPGKLPQTPLDTGIPFPPVFSSSSAVAKSKASLPDFLDHIIASVVENKKT 1350
1351 SDPSKRSCNLTDTQKEVKEMAMGLNVLDPHTSHSWLCDGRLLCLHDPSNK 1400
1401 NNWKIFRECWKQGQPVLVSGVHKKLKSELWKPEAFSQEFGDQDVDLVNCR 1450
1451 NCAIISDVKVRDFWDGFEIICKRLRSEDGQPMVLKLKDWPPGEDFRDMMP 1500
1501 TRFEDLMENLPLPEYTKRDGRLNLASRLPSYFVRPDLGPKMYNAYGLITA 1550
1551 EDRRVGTTNLHLDVSDAVNVMVYVGIPVGEGAHDEEVLKTIDEGDADEVT 1600
1601 KQRIHDGKEKPGALWHIYAAKDAEKIRELLRKVGEEQGQENPPDHDPIHD 1650
1651 QSWYLDQILRKRLFEEYGVQGWAIVQFLGDAVFIPAGAPHQVHNLYSCIK 1700
1701 VAEDFVSPEHVKHCFRLTQEFRHLSNTHTNHEDKLQVKNIIYHAVKDAVG 1750
1751 TLKAHESKLARS 1762
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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