 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9C0C2 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 MKVSTLRESSAMASPLPREMEEELVPTGSEPGDTRAKPPVKPKPRALPAK 50
51 PALPAKPSLLVPVGPRPPRGPLAELPSARKMNMLAGPQPYGGSKRPLPFA 100
101 PRPAVEASTGGEATQETGKEEAGKEEPPPLTPPARCAAPGGVRKAPAPFR 150
151 PASERFAATTVEEILAKMEQPRKEVLASPDRLWGSRLTFNHDGSSRYGPR 200
201 TYGTTTAPRDEDGSTLFRGWSQEGPVKSPAECREEHSKTPEERSLPSDLA 250
251 FNGDLAKAASSELPADISKPWIPSSPAPSSENGGPASPGLPAEASGSGPG 300
301 SPHLHPPDKSSPCHSQLLEAQTPEASQASPCPAVTPSAPSAALPDEGSRH 350
351 TPSPGLPAEGAPEAPRPSSPPPEVLEPHSLDQPPATSPRPLIEVGELLDL 400
401 TRTFPSGGEEEAKGDAHLRPTSLVQRRFSEGVLQSPSQDQEKLGGSLAAL 450
451 PQGQGSQLALDRPFGAESNWSLSQSFEWTFPTRPSGLGVWRLDSPPPSPI 500
501 TEASEAAEAAEAGNLAVSSREEGVSQQGQGAGSAPSGSGSSWVQGDDPSM 550
551 SLTQKGDGESQPQFPAVPLEPLPTTEGTPGLPLQQAEERYESQEPLAGQE 600
601 SPLPLATREAALPILEPVLGQEQPAAPDQPCVLFADAPEPGQALPVEEEA 650
651 VTLARAETTQARTEAQDLCRASPEPPGPESSSRWLDDLLASPPPSGGGAR 700
701 RGAGAELKDTQSPSTCSEGLLGWSQKDLQSEFGITGDPQPSSFSPSSWCQ 750
751 GASQDYGLGGASPRGDPGLGERDWTSKYGQGAGEGSTREWASRCGIGQEE 800
801 MEASSSQDQSKVSAPGVLTAQDRVVGKPAQLGTQRSQEADVQDWEFRKRD 850
851 SQGTYSSRDAELQDQEFGKRDSLGTYSSRDVSLGDWEFGKRDSLGAYASQ 900
901 DANEQGQDLGKRDHHGRYSSQDADEQDWEFQKRDVSLGTYGSRAAEPQEQ 950
951 EFGKSAWIRDYSSGGSSRTLDAQDRSFGTRPLSSGFSPEEAQQQDEEFEK 1000
1001 KIPSVEDSLGEGSRDAGRPGERGSGGLFSPSTAHVPDGALGQRDQSSWQN 1050
1051 SDASQEVGGHQERQQAGAQGPGSADLEDGEMGKRGWVGEFSLSVGPQREA 1100
1101 AFSPGQQDWSRDFCIEASERSYQFGIIGNDRVSGAGFSPSSKMEGGHFVP 1150
1151 PGKTTAGSVDWTDQLGLRNLEVSSCVGSGGSSEARESAVGQMGWSGGLSL 1200
1201 RDMNLTGCLESGGSEEPGGIGVGEKDWTSDVNVKSKDLAEVGEGGGHSQA 1250
1251 RESGVGQTDWSGVEAGEFLKSRERGVGQADWTPDLGLRNMAPGAVCSPGE 1300
1301 SKELGVGQMDWGNNLGLRDLEVTCDPDSGGSQGLRGCGVGQMDWTQDLAP 1350
1351 QNVELFGAPSEAREHGVGGVSQCPEPGLRHNGSLSPGLEARDPLEARELG 1400
1401 VGETSGPETQGEDYSSSSLEPHPADPGMETGEALSFGASPGRCPARPPPS 1450
1451 GSQGLLEEMLAASSSKAVARRESAASGLGGLLEEEGAGAGAAQEEVLEPG 1500
1501 RDSPPSWRPQPDGEASQTEDVDGTWGSSAARWSDQGPAQTSRRPSQGPPA 1550
1551 RSPSQDFSFIEDTEILDSAMYRSRANLGRKRGHRAPVIRPGGTLGLSEAA 1600
1601 DSDAHLFQDSTEPRASRVPSSDEEVVEEPQSRRTRMSLGTKGLKVNLFPG 1650
1651 LSPSALKAKLRPRNRSAEEGELAESKSSQKESAVQRSKSCKVPGLGKPLT 1700
1701 LPPKPEKSSGSEGSSPNWLQALKLKKKKV 1729
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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