 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P34529 from www.uniprot.org...
The NucPred score for your sequence is 0.86 (see score help below)
1 MVRVRADLQCFNPRDYQVELLDKATKKNTIVQLGTGSGKTFIAVLLLKEY 50
51 GVQLFAPLDQGGKRAFFVVEKVNLVEQQAIHIEVHTSFKVGQVHGQTSSG 100
101 LWDSKEQCDQFMKRHHVVVITAQCLLDLIRHAYLKIEDMCVLIFDECHHA 150
151 LGSQHPYRSIMVDYKLLKKDKPVPRVLGLTASLIKAKVAPEKLMEQLKKL 200
201 ESAMDSVIETASDLVSLSKYGAKPYEVVIICKDFEIGCLGIPNFDTVIEI 250
251 FDETVAFVNTTTEFHPDLDLDPRRPIKDSLKTTRAVFRQLGPWAAWRTAQ 300
301 VWEKELGKIIKSQVLPDKTLRFLNMAKTSMITIKRLLEPEMKKIKSIEAL 350
351 RPYVPQRVIRLFEILETFNPEFQKERMKLEKAEHLSAIIFVDQRYIAYSL 400
401 LLMMRHIKSWEPKFKFVNPDYVVGASGRNLASSDSQGLHKRQTEVLRRFH 450
451 RNEINCLIATSVLEEGVDVKQCNLVIKFDRPLDMRSYVQSKGRARRAGSR 500
501 YVITVEEKDTAACDSDLKDFQQIEKILLSRHRTVNNPIEDDSDRFEEFDV 550
551 DSQMEPYVVEKTGATLKMSTAIALINRYCSKLPSDIFTRLVPHNQIIPIE 600
601 ENGVTKYCAELLLPINSPIKHAIVLKNPMPNKKTAQMAVALEACRQLHLE 650
651 GELDDNLLPKGRESIAKLLEHIDEEPDEYAPGIAAKVGSSKRKQLYDKKI 700
701 ARALNESFVEADKECFIYAFELERFREAELTLNPKRRKFEDPFNYEYCFG 750
751 FLSAKEIPKIPPFPVFLRQGNMKVRLIVAPKKTTVTAAQLQEIQLFHNYL 800
801 FTQVLQMCKTGNLEFDGTSNAPLNTLIVPLNKRKDDMSYTINMKYVSEVV 850
851 ANMENMPRIPKDEVRRQYKFNAEDYKDAIVMPWYRNLEQPVFYYVAEILP 900
901 EWRPSSKFPDTHFETFNEYFIKKYKLEIYDQNQSLLDVDFTSTRLNLLQP 950
951 RIQNQPRRSRTVSNSSTSNIPQASASDSKESNTSVPHSSQRQILVPELMD 1000
1001 IHPISATLWNVIAALPSIFYRVNQLLLTDELRETILVKAFGKEKTKLDDN 1050
1051 VEWNSLAYATEYEEKQTIIVKKIQQLRDLNQKSIEDQERETRENDKIDDG 1100
1101 EELFNIGVWDPEEAVRIGVEISSRDDRMDGEDQDTVGLTQGLHDGNISDE 1150
1151 DDELPFVMHDYTARLTSNRNGIGAWSGSESIVPSGWGDWDGPEPDNSPMP 1200
1201 FQILGGPGGLNVQALMADVGRVFDPSTASSSLSQTVQESTVSPPKQLTKE 1250
1251 EEQFKKLQNDLLKQAKERLEALEMSEDMEKPRRLEDTVNLEDYGDDQENQ 1300
1301 EDENTPTNFPKTIDEEIEELSIGARKKQEIDDNAAKTDVLERENCEVLPV 1350
1351 AINEKSRSFSFEKESKAINGRLIRQRSEEYVSHIDSDIGLGVSPCLLLTA 1400
1401 LTTSNAADGMSLERFETIGDSFLKFATTDYLYHTLLDQHEGKLSFARSKE 1450
1451 VSNCNLYRLGKKLGIPQLIVANKFDAHDSWLPPCYIPTCDFKAPNTDDAE 1500
1501 EKDNEIERILDGQVIEEKPENKTGWDIGGDVSKSTTDGIETITFPKQARV 1550
1551 GNDDISPLPYNLLTQQHISDKSIADAVEALIGVHLLTLGPNPTLKVMNWM 1600
1601 GLKVIQKDQKSDVPSPLLRFIDTPTNPNASLNFLNNLWQQFQFTQLEEKI 1650
1651 GYRFKERAYLVQAFTHASYINNRVTGCYQRLEFLGDAVLDYMITRYLFED 1700
1701 SRQYSPGVLTDLRSALVNNTIFASLAVKFEFQKHFIAMCPGLYHMIEKFV 1750
1751 KLCSERNFDTNFNAEMYMVTTEEEIDEGQEEDIEVPKAMGDIFESVAGAI 1800
1801 YLDSGRNLDTTWQVIFHMMRGTIELCCANPPRSPIRELMEFEQSKVRFSK 1850
1851 MERILESGKVRVTVEVVNNMRFTGMGRNYRIAKATAAKRALKYLHQIEQQ 1900
1901 RRQSPSLTTV 1910
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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