 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P22374 from www.uniprot.org...
The NucPred score for your sequence is 0.36 (see score help below)
1 QFSIKVMQSSYVGLRSTVQFLQLSQIIWIKSRIAKSENDYINSMKKFLSH 50
51 KKQNNRKFHTRSMSNGLGSLNLQKRPTPSPTVLNNKFLPTRNQYHSEDIN 100
101 NNILFDIIIKETDKGLKKCVLIGLNLTTNKIFNMEYIDLNTSNRKFKIFV 150
151 ANNLINIKNNGINIDNLYIPKRINSKTLTDLITLSFPNIKVQWYLKSEIT 200
201 NLFLKSDYTNFIKEINERKTLGKSILSKLIIYYNDSSPHCNIGKSSRKVT 250
251 AISHTKRDIHTSTENNHKKDLFGWHRFNSSNYYDCIDSGALTIEINKLFE 300
301 YYKDNFTQPFFVVNAKIKFPTGNVRSIGFGNVTTLTDKETLIKTLAIFLE 350
351 REDIHTVMSYDEGDIDESKFPKGSLSFDFKPLKTIEGTKYANYTFPIKKD 400
401 IVVKDINKKINFNGLDLPKTMDLSKWPNLKLNKDKTSGEIRMTIKNKNNQ 450
451 SYDIIGHMIINDGENVITFNRAVDNSIIKIFTVTDSMGNTNDPNLFKRIV 500
501 EEKGNQTVYVYENNETVCVVQDKKFGFISKIAKNKTVNLKSISTLDLETR 550
551 MDTNNRLIPICMSYYNNKKLNTFLFKDDWQEEMLAAFKTLLKSTNHGKKF 600
601 YVHNLAHFDSVFILDTLSKLGKIDIIMRDDKIMKLKITFKIPGKNTEYSI 650
651 SFLDSLLMLPNSLDNLSKAFNIENKKSVFPLKFTNGAVTPFNYIGAVPGY 700
701 EYFYNTPNKKFTKDDYKKYCKDFNNNWDFNKELKNYCEIDCLALHDILTL 750
751 FAKMIHNEFSVDITRYVSLSSITFAIFRTNFLPENKIPNITCTKLHYILK 800
801 QAYTGGYCDVFKPEGKNIHSYDINSLYPSAMAKFDMPTGTPLHILGDPYK 850
851 FTKDPFGFVFAEVTAPDLKVPIIQTRVQTSGGVRTVAPIGTFKGWYLLDE 900
901 LINAKKYGYTFKISEAYLFERLNIFKEYIHRLYTIKSSYTPDDPMYFIAK 950
951 LLMNSLYGRFGMDPITIKYSVLTPEESEEKLKNSSCIEATTLPSGNVLFK 1000
1001 ENKPLGEFSNLNTSVPISAAIAAYSRMIMSEYLIKYADNLYAVDTDGIKV 1050
1051 DTEIDKKYVSDKELGLMKHEYTFKEAVFVAPKVYGGLFDKPYKNKVEIVK 1100
1101 VKGLKEPIQYSDLKDVYIKSLLKLFIILNFLRQLALSTIVIKEQPYSLRV 1150
1151 SSFKRVLVFNESGKIISTLPLKLENDKIVSNPHLIVNSEGNPSAFKLSLI 1200
1201 KI 1202
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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