 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UPW8 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MSLLCVGVKKAKFDGAQEKFNTYVTLKVQNVKSTTIAVRGSQPSWEQDFM 50
51 FEINRLDLGLTVEVWNKGLIWDTMVGTVWIPLRTIRQSNEEGPGEWLTLD 100
101 SQVIMADSEICGTKDPTFHRILLDTRFELPLDIPEEEARYWAKKLEQLNA 150
151 MRDQDEYSFQDEQDKPLPVPSNQCCNWNYFGWGEQHNDDPDSAVDDRDSD 200
201 YRSETSNSIPPPYYTTSQPNASVHQYSVRPPPLGSRESYSDSMHSYEEFS 250
251 EPQALSPTGSSRYASSGELSQGSSQLSEDFDPDEHSLQGSDMEDERDRDS 300
301 YHSCHSSVSYHKDSPRWDQDEEELEEDLEDFLEEEELPEDEEELEEEEEE 350
351 VPDDLGSYAQREDVAVAEPKDFKRISLPPAAPGKEDKAPVAPTEAPDMAK 400
401 VAPKPATPDKVPAAEQIPEAEPPKDEESFRPREDEEGQEGQDSMSRAKAN 450
451 WLRAFNKVRMQLQEARGEGEMSKSLWFKGGPGGGLIIIDSMPDIRKRKPI 500
501 PLVSDLAMSLVQSRKAGITSALASSTLNNEELKNHVYKKTLQALIYPISC 550
551 TTPHNFEVWTATTPTYCYECEGLLWGIARQGMRCTECGVKCHEKCQDLLN 600
601 ADCLQRAAEKSSKHGAEDRTQNIIMVLKDRMKIRERNKPEIFELIQEIFA 650
651 VTKTAHTQQMKAVKQSVLDGTSKWSAKISITVVCAQGLQAKDKTGSSDPY 700
701 VTVQVGKTKKRTKTIYGNLNPVWEENFHFECHNSSDRIKVRVWDEDDDIK 750
751 SRVKQRFKRESDDFLGQTIIEVRTLSGEMDVWYNLDKRTDKSAVSGAIRL 800
801 HISVEIKGEEKVAPYHVQYTCLHENLFHFVTDVQNNGVVKIPDAKGDDAW 850
851 KVYYDETAQEIVDEFAMRYGVESIYQAMTHFACLSSKYMCPGVPAVMSTL 900
901 LANINAYYAHTTASTNVSASDRFAASNFGKERFVKLLDQLHNSLRIDLSM 950
951 YRNNFPASSPERLQDLKSTVDLLTSITFFRMKVQELQSPPRASQVVKDCV 1000
1001 KACLNSTYEYIFNNCHELYSREYQTDPAKKGEVLPEEQGPSIKNLDFWSK 1050
1051 LITLIVSIIEEDKNSYTPCLNQFPQELNVGKISAEVMWNLFAQDMKYAME 1100
1101 EHDKHRLCKSADYMNLHFKVKWLYNEYVTELPAFKDRVPEYPAWFEPFVI 1150
1151 QWLDENEEVSRDFLHGALERDKKDGFQQTSEHALFSCSVVDVFSQLNQSF 1200
1201 EIIKKLECPDPQIVGHYMRRFAKTISNVLLQYADIISKDFASYCSKEKEK 1250
1251 VPCILMNNTQQLRVQLEKMFEAMGGKELDAEASDILKELQVKLNNVLDEL 1300
1301 SRVFATSFQPHIEECVKQMGDILSQVKGTGNVPASACSSVAQDADNVLQP 1350
1351 IMDLLDSNLTLFAKICEKTVLKRVLKELWKLVMNTMEKTIVLPPLTDQTM 1400
1401 IGNLLRKHGKGLEKGRVKLPSHSDGTQMIFNAAKELGQLSKLKDHMVREE 1450
1451 AKSLTPKQCAVVELALDTIKQYFHAGGVGLKKTFLEKSPDLQSLRYALSL 1500
1501 YTQATDLLIKTFVQTQSAQGLGVEDPVGEVSVHVELFTHPGTGEHKVTVK 1550
1551 VVAANDLKWQTSGIFRPFIEVNIIGPQLSDKKRKFATKSKNNSWAPKYNE 1600
1601 SFQFTLSADAGPECYELQVCVKDYCFAREDRTVGLAVLQLRELAQRGSAA 1650
1651 CWLPLGRRIHMDDTGLTVLRILSQRSNDEVAKEFVKLKSDTRSAEEGGAA 1700
1701 PAP 1703
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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