 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P21447 from www.uniprot.org...
The NucPred score for your sequence is 0.26 (see score help below)
1 MELEEDLKGRADKNFSKMGKKSKKEKKEKKPAVSVLTMFRYAGWLDRLYM 50
51 LVGTLAAIIHGVALPLMMLIFGDMTDSFASVGNVSKNSTNMSEADKRAMF 100
101 AKLEEEMTTYAYYYTGIGAGVLIVAYIQVSFWCLAAGRQIHKIRQKFFHA 150
151 IMNQEIGWFDVHDVGELNTRLTDDVSKINEGIGDKIGMFFQAMATFFGGF 200
201 IIGFTRGWKLTLVILAISPVLGLSAGIWAKILSSFTDKELHAYAKAGAVA 250
251 EEVLAAIRTVIAFGGQKKELERYNNNLEEAKRLGIKKAITANISMGAAFL 300
301 LIYASYALAFWYGTSLVISKEYSIGQVLTVFFSVLIGAFSVGQASPNIEA 350
351 FANARGAAYEVFKIIDNKPSIDSFSKSGHKPDNIQGNLEFKNIHFSYPSR 400
401 KEVQILKGLNLKVKSGQTVALVGNSGCGKSTTVQLMQRLYDPLDGMVSID 450
451 GQDIRTINVRYLREIIGVVSQEPVLFATTIAENIRYGREDVTMDEIEKAV 500
501 KEANAYDFIMKLPHQFDTLVGERGAQLSGGQKQRIAIARALVRNPKILLL 550
551 DEATSALDTESEAVVQAALDKAREGRTTIVIAHRLSTVRNADVIAGFDGG 600
601 VIVEQGNHDELMREKGIYFKLVMTQTAGNEIELGNEACKSKDEIDNLDMS 650
651 SKDSGSSLIRRRSTRKSICGPHDQDRKLSTKEALDEDVPPASFWRILKLN 700
701 STEWPYFVVGIFCAIINGGLQPAFSVIFSKVVGVFTNGGPPETQRQNSNL 750
751 FSLLFLILGIISFITFFLQGFTFGKAGEILTKRLRYMVFKSMLRQDVSWF 800
801 DDPKNTTGALTTRLANDAAQVKGATGSRLAVIFQNIANLGTGIIISLIYG 850
851 WQLTLLLLAIVPIIAIAGVVEMKMLSGQALKDKKELEGSGKIATEAIENF 900
901 RTVVSLTREQKFETMYAQSLQIPYRNAMKKAHVFGITFSFTQAMMYFSYA 950
951 ACFRFGAYLVTQQLMTFENVLLVFSAIVFGAMAVGQVSSFAPDYAKATVS 1000
1001 ASHIIRIIEKTPEIDSYSTQGLKPNMLEGNVQFSGVVFNYPTRPSIPVLQ 1050
1051 GLSLEVKKGQTLALVGSSGCGKSTVVQLLERFYDPMAGSVFLDGKEIKQL 1100
1101 NVQWLRAQLGIVSQEPILFDCSIAENIAYGDNSRVVSYEEIVRAAKEANI 1150
1151 HQFIDSLPDKYNTRVGDKGTQLSGGQKQRIAIARALVRQPHILLLDEATS 1200
1201 ALDTESEKVVQEALDKAREGRTCIVIAHRLSTIQNADLIVVIQNGKVKEH 1250
1251 GTHQQLLAQKGIYFSMVSVQAGAKRS 1276
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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