 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O75147 from www.uniprot.org...
The NucPred score for your sequence is 0.25 (see score help below)
1 MKASSGDQGSPPCFLRFPRPVRVVSGAEAELKCVVLGEPPPVVVWEKGGQ 50
51 QLAASERLSFPADGAEHGLLLTAALPTDAGVYVCRARNAAGEAYAAAAVT 100
101 VLEPPASDPELQPAERPLPSPGSGEGAPVFLTGPRSQWVLRGAEVVLTCR 150
151 AGGLPEPTLYWEKDGMALDEVWDSSHFALQPGRAEDGPGASLALRILAAR 200
201 LPDSGVYVCHARNAHGHAQAGALLQVHQPPESPPADPDEAPAPVVEPLKC 250
251 APKTFWVNEGKHAKFRCYVMGKPEPEIEWHWEGRPLLPDRRRLMYRDRDG 300
301 GFVLKVLYCQAKDRGLYVCAARNSAGQTLSAVQLHVKEPRLRFTRPLQDV 350
351 EGREHGIAVLECKVPNSRIPTAWFREDQRLLPCRKYEQIEEGTVRRLIIH 400
401 RLKADDDGIYLCEMRGRVRTVANVTVKGPILKRLPRKLDVLEGENAVLLV 450
451 ETLEAGVEGRWSRDGEELPVICQSSSGHMHALVLPGVTREDAGEVTFSLG 500
501 NSRTTTLLRVKCVKHSPPGPPILAEMFKGHKNTVLLTWKPPEPAPETPFI 550
551 YRLERQEVGSEDWIQCFSIEKAGAVEVPGDCVPSEGDYRFRICTVSGHGR 600
601 SPHVVFHGSAHLVPTARLVAGLEDVQVYDGEDAVFSLDLSTIIQGTWFLN 650
651 GEELKSNEPEGQVEPGALRYRIEQKGLQHRLILHAVKHQDSGALVGFSCP 700
701 GVQDSAALTIQESPVHILSPQDRVSLTFTTSERVVLTCELSRVDFPATWY 750
751 KDGQKVEESELLVVKMDGRKHRLILPEAKVQDSGEFECRTEGVSAFFGVT 800
801 VQDPPVHIVDPREHVFVHAITSECVMLACEVDREDAPVRWYKDGQEVEES 850
851 DFVVLENEGPHRRLVLPATQPSDGGEFQCVAGDECAYFTVTITDVSSWIV 900
901 YPSGKVYVAAVRLERVVLTCELCRPWAEVRWTKDGEEVVESPALLLQKED 950
951 TVRRLVLPAVQLEDSGEYLCEIDDESASFTVTVTEPPVRIIYPRDEVTLI 1000
1001 AVTLECVVLMCELSREDAPVRWYKDGLEVEESEALVLERDGPRCRLVLPA 1050
1051 AQPEDGGEFVCDAGDDSAFFTVTVTAPPERIVHPAARSLDLHFGAPGRVE 1100
1101 LRCEVAPAGSQVRWYKDGLEVEASDALQLGAEGPTRTLTLPHAQPEDAGE 1150
1151 YVCETRHEAITFNVILAEPPVQFLALETTPSPLCVAPGEPVVLSCELSRA 1200
1201 GAPVVWSHNGRPVQEGEGLELHAEGPRRVLCIQAAGPAHAGLYTCQSGAA 1250
1251 PGAPSLSFTVQVAEPPVRVVAPEAAQTRVRSTPGGDLELVVHLSGPGGPV 1300
1301 RWYKDGERLASQGRVQLEQAGARQVLRVQGARSGDAGEYLCDAPQDSRIF 1350
1351 LVSVEEPLLVKLVSELTPLTVHEGDDATFRCEVSPPDADVTWLRNGAVVT 1400
1401 PGPQVEMAQNGSSRILTLRGCQLGDAGTVTLRAGSTATSARLHVRETELL 1450
1451 FLRRLQDVRAEEGQDVCLEVETGRVGAAGAVRWVRGGQPLPHDSRLSMAQ 1500
1501 DGHIHRLFIHGVILADQGTYGCESHHDRTLARLSVRPRQLRVLRPLEDVT 1550
1551 ISEGGSATFQLELSQEGVTGEWARGGVQLYPGPKCHIHSDGHRHRLVLNG 1600
1601 LGLADSGCVSFTADSLRCAARLIVREVPVTIVRGPHDLEVTEGDTATFEC 1650
1651 ELSQALADVTWEKDGNALTPSPRLRLQALGTRRLLQLRRCGPSDAGTYSC 1700
1701 AVGTARAGPVRLTVRERTVAVLSELRSVSAREGDGATFECTVSEVETTGR 1750
1751 WELGGRPLRPGARVRIRQEGKKHILVLSELRAEDAGEVRFQAGPAQSLAL 1800
1801 LEVEALPLQMCRHPPREKTVLVGRRAVLEVTVSRSGGHVCWLREGAELCP 1850
1851 GDKYEMRSHGPTHSLVIHDVRPEDQGTYCCQAGQDSTHTRLLVEGN 1896
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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