 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P70206 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MPLPPLSSRTLLLLLLLLLRGVWIAISSPPAGLGPQPAFRTFVASDWGLT 50
51 HLVVHEQTGEVYVGAVNRIYKLSGNLTLLRAHVTGPVEDNEKCYPPPSVQ 100
101 SCPHGLGSTDNVNKLLLLDYAANRLLACGSASQGICQFLRLDDLFKLGEP 150
151 HHRKEHYLSSVREAGSMAGVLIAGPPGQGQAKLFVGTPIDGKSEYFPTLS 200
201 SRRLMANEEDADMFGFVYQDEFVSSQLKIPSDTLSKFPAFDIYYVYSFRS 250
251 EQFVYYLTLQLDTQLTSPDAAGEHFFTSKIVRLCVNDPKFYSYVEFPIGC 300
301 EQAGVEYRLVQDAYLSRPGQALAKQLGLAEDEEVLFTVFAQGQKNRVKPP 350
351 KESALCLFTLRAIKEKIKERIQSCYRGEGKLSLPWLLNKELGCINSPLQI 400
401 DDDFCGQDFNQPLGGTVTIEGTPLFVDKEDGLTAVAAYDYQGRTVVFAGT 450
451 RSGRIRKILVDLANPSGRPALAYESVVAQEGNPILRDLVLSPNRQYLYAM 500
501 TEKQVTQVPVESCVQYTSCELCLGSRDPHCGWCVLHSICSRQDACERAEE 550
551 PQRFASDLLQCVQLTVQPRNVSVTMSQVPLVLQAWNVPDLSAGVNCSFED 600
601 FTETESILEDGRIHCHSPSAREVAPITQGQGDQRVVKLYLKSKETGKKFA 650
651 SVDFVFYNCSVHQSCLACVNGSFPCHWCKYRHVCTNNAADCAFLEGRVNM 700
701 SEDCPQILPSTHIYVPVGVVKPITLAARNLPQPQSGQRGYECLFHIPGSP 750
751 ARVTALRFNSSSLQCQNSSYSYEGNDVSDLPVNLSVVWNGNFVIDNPQNI 800
801 QAHLYKCPALRQSCGLCLKADPRFECGWCVAERRCSLRHHCPADSPASWM 850
851 HAHHGSSRCTDPKILKLSPETGPRQGGTRLTITGENLGLRFEDVRLGVHV 900
901 GKVLCSPVESEYISAEQIVCEIGDASTLRAHDALVEVCVRDCSLHYRALS 950
951 PKRFTFVTPTFYRVSPSRGPLSGGTWIGIEGSHLNAGSDVAVSIGGRPCS 1000
1001 FSWRNSREIRCLTPPGHTPGSAPIVININRAQLSNPEVKYNYTEDPTILR 1050
1051 IDPEWSINSGGTLLTVTGTNLATVREPRIRAKYGGIERENSCMVYNDTTM 1100
1101 VCRAPSIDNPKRSPPELGERPDEIGFIMDNVRTLLVLNSSSFLYYPDPVL 1150
1151 EPLSPTGLLELKPSSPLILKGRNLLPPAPGNSRLNYTVLIGSTPCILTVS 1200
1201 ETQLLCEAPNLTGQHKVTVRAGGFEFSPGMLQVYSDSLLTLPAIVGIGGG 1250
1251 GGLLLLVIVAVLIAYKRKSRDADRTLKRLQLQMDNLESRVALECKEAFAE 1300
1301 LQTDIHELTSDLDGAGIPFLDYRTYAMRVLFPGIEDHPVLKEMEVQANVE 1350
1351 KSLTLFGQLLTKKHFLLTFIRTLEAQRSFSMRDRGNVASLIMTALQGEME 1400
1401 YATGVLKQLLSDLIEKNLESKNHPKLLLRRTESVAEKMLTNWFTFLLYKF 1450
1451 LKECAGEPLFMLYCAIKQQMEKGPIDAITGEARYSLSEDKLIRQQIDYKT 1500
1501 LTLNCVNPEHENAPEVPVKGLNCDTVTQVKEKLLDAVYKGVPYSQRPKAG 1550
1551 DMDLEWRQGRMARIILQDEDVTTKIDNDWKRLNTLAHYQVTDGSSVALVP 1600
1601 KQTSAYNISNSSTFTKSLSRYESMLRTASSPDSLRSRTPMITPDLESGTK 1650
1651 LWHLVKNHDHLDQREGDRGSKMVSEIYLTRLLATKGTLQKFVDDLFETIF 1700
1701 STAHRGSALPLAIKYMFDFLDEQADKHQIHDSDVRHTWKSNCLPLRFWVN 1750
1751 VIKNPQFVFDIHKNSITDACLSVVAQTFMDSCSTSEHKLGKDSPSNKLLY 1800
1801 AKDIPNYKSWVERYYADIAKMPAISDQDMSAYLAEQSRLHLSQFNSMSAL 1850
1851 HEIYSYIAKYKDEILVALEKDEQARRQRLRSKLEQVVDTMALSS 1894
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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