 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8BMJ2 from www.uniprot.org...
The NucPred score for your sequence is 0.21 (see score help below)
1 MAGRKGTAKVDFLKEIEKEAQQKWEAEKVFEVSASRLEKQKQSSKGKYFV 50
51 TFPYPYMNGRLHLGHTFSLSKCEFAVGYQRLKGKSCLFPFGLHCTGMPIK 100
101 ACADKLKREIELYGCPPDFPEEEEEEEESSAKPGDIVVRDKAKGKKSKAA 150
151 AKAGSSKYQWDIMKSLGLSDDDIVKFSEAEHWLDYFPPLAVQDLKTIGLK 200
201 VDWRRSFITTDVNPYYDSFVRWQFLTLRERNKIKFGKRYTIYSPKDGQPC 250
251 MDHDRQTGEGVGPQEYTLVKLKVLEPYPSKLSGLKGKNIFLVAATLRPET 300
301 MFGQTNCWVRPDMKYIGFETANGDIFICTQRAARNMSYQGFTKHNGVVPV 350
351 VKELMGEEILGASLSAPLTCYKVVYVLPMLTIKEDKGTGVVTSVPSDSPD 400
401 DLAALRDLKKKQALRTKFGIRDDMVLPFEPVPVLEIPGIGNLPAVTVCDE 450
451 LKIQSQNDREKLAEAKEKLYLRGFYDGVMLVDGFKGQKIQHVKKTIQKNM 500
501 IDAGDALIYMEPEKQVMSRSADECVVALCDQWYLDYGDENWKKQTFQCLK 550
551 NMETFCEESRKNFEASLDWLQEHACSRTYGLGTRLPWDEQWLIESLSDST 600
601 IYMAFYTVAHLLQGGDLNGQAESPLGIRPQQMTKDVWDYVFFKDAPFPKT 650
651 QIPKEKLDQLKQEFEFWYPVDLRASGKDLIPNHLSYYIYNHVAMWPEQSD 700
701 KWPVSVRANGHLLLNSEKMSKSTGNFLTLSQAVDKFSADGMRLALADAGD 750
751 TVEDANFVEAMADAGILRLYTWVEWVKEMLASCSSLRSGPADSFNDRVFA 800
801 SEMNAGIIKTDQNYEKMMFKEALKTGFFEFQAAKDKYRELATEGMHRELV 850
851 FRFIEVQTILLTPFCPHLCEHIWTLLGKPDSIMHASWPVAGPVDESLIRS 900
901 SQYLMEVAHDLRLRLKNYMMPAKGKKTDKQPAQRPSHCTIYVAKNYPVWQ 950
951 HITLTTLRSHFEANNGKLPDNKVIASELGSLPELKKYMKKVMPFVAMIKE 1000
1001 NMEKKGPRVLDLELEFDEQAVLMENIVYLTNSLELEHIEVKFASEAEDKV 1050
1051 REECCPGKPLNVFRTEPGVPVSLVNPQPSSGHFSTKIDIRQGDSCESIIR 1100
1101 RLMKTDRGIKDLSKVKLMRFDDPLLGPRRVPVLGREHSEKTLISENAVFH 1150
1151 VDLVSKKVHLTENGLRTDIGDTMVYLVH 1178
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.