 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P25386 from www.uniprot.org...
The NucPred score for your sequence is 0.83 (see score help below)
1 MDIIQGLIQQPKIQSVDETIPTLCDRVENSTLISDRRSAVLGLKAFSRQY 50
51 RESVIASGLKPLLNTLKRDYMDEDSVKAILETILILFIRGDGHDDLTRGW 100
101 ISQQSRLQNGKYPSPLVMKQEKEQVDQFSLWIADALTQSEDLIHLLVEFW 150
151 EIDNFHIRLYTIQLLEAVMATRPLKARSALISLPTSISTMVSLLDDMHEP 200
201 IRDEAILLLMAVVNDSPHVQKLVAFENIFERLFSIIEEEGGLRGSLVVND 250
251 CLSLINNILKYNTSNQTLFLETGNLPKLAHLLSEPISQDEVFFWNDQRIV 300
301 NINTALDIVSLTVEPGNTVTTKHQNALLDSSVLMVVLRLAFFHNIPKKVR 350
351 PVALLTAANMVRSNEHAQLEFSKIDVPYFDPSLPVNSTANGGPIKLIPVV 400
401 SILINWMLYANSVHTFDTRVACSRLLKAYFMDNFDLQRDFLLKQVQLCNN 450
451 STNNVGDNAKENGGSNKSDKESDSDKDTDGKDGTEYEGSFKANLFEVLLN 500
501 YDAELNLNPFKLFFTTDIFMFFFQQDHKYSEELREITRNVTTGNDLEDEE 550
551 PLKAIQTISELLTTSLTAADIRIPISYLTFLIYWLFGDFKATNDFLSDKS 600
601 VIKSLLSFSYQIQDEDVTIKCLVTMLLGVAYEFSSKESPFPRKEYFEFIT 650
651 KTLGKDNYASRIKQFKKDSYFSKVDMNEDSILTPELDETGLPKVYFSTYF 700
701 IQLFNENIYRIRTALSHDPDEEPINKISFEEVEKLQRQCTKLKGEITSLQ 750
751 TETESTHENLTEKLIALTNEHKELDEKYQILNSSHSSLKENFSILETELK 800
801 NVRDSLDEMTQLRDVLETKDKENQTALLEYKSTIHKQEDSIKTLEKGLET 850
851 ILSQKKKAEDGINKMGKDLFALSREMQAVEENCKNLQKEKDKSNVNHQKE 900
901 TKSLKEDIAAKITEIKAINENLEEMKIQCNNLSKEKEHISKELVEYKSRF 950
951 QSHDNLVAKLTEKLKSLANNYKDMQAENESLIKAVEESKNESSIQLSNLQ 1000
1001 NKIDSMSQEKENFQIERGSIEKNIEQLKKTISDLEQTKEEIISKSDSSKD 1050
1051 EYESQISLLKEKLETATTANDENVNKISELTKTREELEAELAAYKNLKNE 1100
1101 LETKLETSEKALKEVKENEEHLKEEKIQLEKEATETKQQLNSLRANLESL 1150
1151 EKEHEDLAAQLKKYEEQIANKERQYNEEISQLNDEITSTQQENESIKKKN 1200
1201 DELEGEVKAMKSTSEEQSNLKKSEIDALNLQIKELKKKNETNEASLLESI 1250
1251 KSVESETVKIKELQDECNFKEKEVSELEDKLKASEDKNSKYLELQKESEK 1300
1301 IKEELDAKTTELKIQLEKITNLSKAKEKSESELSRLKKTSSEERKNAEEQ 1350
1351 LEKLKNEIQIKNQAFEKERKLLNEGSSTITQEYSEKINTLEDELIRLQNE 1400
1401 NELKAKEIDNTRSELEKVSLSNDELLEEKQNTIKSLQDEILSYKDKITRN 1450
1451 DEKLLSIERDNKRDLESLKEQLRAAQESKAKVEEGLKKLEEESSKEKAEL 1500
1501 EKSKEMMKKLESTIESNETELKSSMETIRKSDEKLEQSKKSAEEDIKNLQ 1550
1551 HEKSDLISRINESEKDIEELKSKLRIEAKSGSELETVKQELNNAQEKIRI 1600
1601 NAEENTVLKSKLEDIERELKDKQAEIKSNQEEKELLTSRLKELEQELDST 1650
1651 QQKAQKSEEERRAEVRKFQVEKSQLDEKAMLLETKYNDLVNKEQAWKRDE 1700
1701 DTVKKTTDSQRQEIEKLAKELDNLKAENSKLKEANEDRSEIDDLMLLVTD 1750
1751 LDEKNAKYRSKLKDLGVEISSDEEDDEEDDEEDEEEGQVA 1790
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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