 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q62768 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MSLLCVGVKKAKFDGAQEKFNTYVTLKVQNVKSTTIAVRGSQPSWEQDFM 50
51 FEINRLDLGLTVEVWNKGLIWDTMVGTVWIPLRTIRQSNEEGPGEWLTLD 100
101 SQAIMADSEICGTKDPTFHRILLDAHFELPLDIPEEEARYWAKKLEQLNA 150
151 MRDQDEYSFQDQQDKPLPVPSSQCCNWNYFGWGEQNDDPDSAVDDRDSDY 200
201 RSETSNSIPPPYYTTSQPNASVHQYSVRPPPLGSRESYSDSMHSYEEFSE 250
251 PRALSPTGSSRYASSGELSQGSSQLSEDFDPDEHSLQGSELDDERDRDSY 300
301 HSCHSSVSYHKDSPRWDQDEEDLEDLEDLEDEELPEEEELEEEELEEEEE 350
351 LEEEELELEEEEEVPDDLASYTQQEDTTVAEPKEFKRISFPTAAPQKEDK 400
401 VSAVPIEAPDVSKGIPKAATPEEKAAAECAQEAEPPKSEESFRSREAEEG 450
451 QEGQDAMSRAKANWLRAFNKVRMQLQEARGEGEMSKSLWFKGGPGGGLII 500
501 IDSMPDIRKRKPIPLVSDLAMSLVQSRKAGITSALASSTLNNEELKNHVY 550
551 KKTLQALIYPISCTTPHNFEVWTATTPTYCYECEGLLWGIARQGMRCTEC 600
601 GVKCHEKCQDLLNADCLQRAAEKSSKHGAEDRTQNIIMVLKDRMKIRERN 650
651 KPEIFELIQEVFAVTKSAHTQQMKAVKQSVLDGTSKWSAKISITVVCAQG 700
701 LQAKDKTGSSDPYVTVQVGKTKKRTKTIYGNLNPVWEENFHFECHNSSDR 750
751 IKVRVLDEDDDIKSRVKQRFKRESDDFLGQTIIEVRTLSGEMDVWYNLDK 800
801 RTDKSAVSGAIRLHISVEIKGEEKVAPYHVQYTCLHENLFHFVTDVQNNG 850
851 VVKIPDAKGDDAWKVYYDETAQEIVDEFAMRYGVESIYQAMTHFACLSSK 900
901 YMCPGVPAVMSTLLANINAYYAHTTASTNVSASDRFAASNFGKERFVKLL 950
951 DQLHNSLRIDLSMYRNNFPASSPERLQDLKSTVDLLTSITFFRMKVQELQ 1000
1001 SPPRASQVVKDCVKACLNSTYEYIFNNCHELYGREYQTDPAKKGEVPPEE 1050
1051 QGPSIKNLDFWSKLITLIVSIIEEDKNSYTPCLNQFPQELNVGKISAEVM 1100
1101 WSLFAQDMKYAMEEHDKHRLCKSADYMNLHFKVKWLYNEYVAELPTFKDR 1150
1151 VPEYPAWFEPFVIQWLDENEEVSRDFLHGALERDKKDGFQQTSEHALFSC 1200
1201 SVVDVFSQLNQSFEIIKKLECPDPQIVGHYMRRFAKTISNVLLQYADIVS 1250
1251 KDFASYCSKEKEKVPCILMNNTQQLRVQLEKMFEAMGGKELDAEASGTLK 1300
1301 ELQVKLNNVLDELSHVFATSFQPHIEECVRQMGDILSQVKGTGNVPASAC 1350
1351 SSVAQDADNVLQPIMDLLDSNLTLFAKICEKTVLKRVLKELWKLVMNTME 1400
1401 RTIVLPPLTDQTMIGTLLRKHGKGLEKGRVKLPSHSDGTQMIFNAAKELG 1450
1451 QLSKLKDHMVREEAKSLTPKQCAVVELALDTIKQYFHAGGVGLKKTFLEK 1500
1501 SPDLQSLRYALSLYTQATDLLIKTFVQTQSAQVHGGKGTRFTLSEDVCPE 1550
1551 MGSGVEDPVGEVSVHVELFTHPGTGEQKVTVKVVAANDLKWQTSGIFRPF 1600
1601 IEVNIVGPQLSDKKRKFATKSKNNSWAPKYNESFQFSLSADAGPECYELQ 1650
1651 VCVKDYCFAREDRTVELAVLQLRELAQRGSAACWLPLGRRIHMDDTGLTV 1700
1701 LRILSQRSNDEVAKEFVKLKSDTRSAEEGGAAPAP 1735
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.) |
Go back to the NucPred Home Page.