 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O70481 from www.uniprot.org...
The NucPred score for your sequence is 0.76 (see score help below)
1 MADEEMDGAERMDVSPEPPLAPQRPASWWDQQVDFYTAFLHHLAQLVPEI 50
51 YFAEMDPDLEKQEESVQMSILTPLEWYLFGEDPDICLEKLKHSGAFQLCG 100
101 KVFKSGETTYSCRDCAIDPTCVLCMDCFQSSVHKNHRYKMHTSTGGGFCD 150
151 CGDTEAWKTGPFCVDHEPGRAGTTKESLHCPLNEEVIAQARRIFPSVIKY 200
201 IVEMTIWEEEKELPPELQIREKNERYYCVLFNDEHHSYDHVIYSLQRALD 250
251 CELAEAQLHTTAIDKEGRRAVKAGVYATCQEAKEDIKSHSENVSQHPLHV 300
301 EVLHSVVMAHQKFALRLGSWMNKIMSYSSDFRQIFCQACLVEEPGSENPC 350
351 LISRLMLWDAKLYKGARKILHELIFSSFFMEMEYKKLFAMEFVKYYKQLQ 400
401 KEYISDDHERSISITALSVQMLTVPTLARHLIEEQNVISVITETLLEVLP 450
451 EYLDRNNKFNFQGYSQDKLGRVYAVICDLKYILISKPVIWTERLRAQFLE 500
501 GFRSFLKILTCMQGMEEIRRQVGQHIEVDPDWEAAIAIQMQLKNILLMFQ 550
551 EWCACDEDLLLVAYKECHKAVMRCSTNFMSSTKTVVQLCGHSLETKSYKV 600
601 SEDLVSIHLPLSRTLAGLHVRLSRLGAISRLHEFVPFDGFQVEVLVEYPL 650
651 RCLVLVAQVVAEMWRRNGLSLISQVFYYQDVKCREEMYDKDIIMLQIGAS 700
701 IMDPNKFLLLVLQRYELTDAFNKTISTKDQDLIKQYNTLIEEMLQVLIYI 750
751 VGERYVPGVGNVTREEVIMREITHLLCIEPMPHSAIARNLPENENNETGL 800
801 ENVINKVATFKKPGVSGHGVYELKDESLKDFNMYFYHYSKTQHSKAEHMQ 850
851 KKRRKQENKDEALPPPPPPEFCPAFSKVVNLLSCDVMMYILRTIFERAVD 900
901 MESNLWTEGMLQMAFHILALGLLEEKQQLQKAPEEEVAFDFYHKASRLGS 950
951 SAMNAQNIQMLLEKLKGIPQLESQKDMITWILQMFDTVKRLREKSCLVVA 1000
1001 TTSGLECVKSEEITHDKEKAERKRKAEAARLHRQKIMAQMSALQKNFIET 1050
1051 HKLMYDNTSEVTGKEDSIMEEESTSAVSEASRIALGPKRGPAVTEKEVLT 1100
1101 CILCQEEQEVKLENNAMVLSACVQKSTALTQHRGKPVDHLGETLDPLFMD 1150
1151 PDLAHGTYTGSCGHVMHAVCWQKYFEAVQLSSQQRIHVDLFDLESGEYLC 1200
1201 PLCKSLCNTVIPIIPLQPQKINSENAEALAQLLTLARWIQTVLARISGYN 1250
1251 IKHAKGEAPAVPVLFNQGMGDSTFEFHSILSFGVQSSVKYSNSIKEMVIL 1300
1301 FATTIYRIGLKVPPDELDPRVPMMTWSTCAFTIQAIENLLGDEGKPLFGA 1350
1351 LQNRQHNGLKALMQFAVAQRTTCPQVLIHKHLARLLSVILPNLQSENTPG 1400
1401 LLSVDLFHVLVGAVLAFPSLYWDDTVDLQPSPLSSSYNHLYLFHLITMAH 1450
1451 MLQILLTTDTDLSSGPPLAEGEEDSEEARCASAFFVEVSQHTDGLAGCGA 1500
1501 PGWYLWLSLRNGITPYLRCAALLFHYLLGVAPPEELFANSAEGEFSALCS 1550
1551 YLSLPTNLFLLFQEYWDTIRPLLQRWCGDPALLKSLKQKSAVVRYPRKRN 1600
1601 SLIELPEDYSCLLNQASHFRCPRSADDERKHPVLCLFCGAILCSQNICCQ 1650
1651 EIVNGEEVGACVFHALHCGAGVCIFLKIRECRVVLVEGKARGCAYPAPYL 1700
1701 DEYGETDPGLKRGNPLHLSRERYRKLHLVWQQHCIIEEIARSQETNQMLF 1750
1751 GFNWQLL 1757
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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