 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q01285 from www.uniprot.org...
The NucPred score for your sequence is 0.72 (see score help below)
1 MSLPRRPGPSPPHEEPRRYRQSGSRRSRPPPADVETGYAPMAGERPSQQQ 50
51 RVPSISSFPETLPSPNPNVERDPLAPTPEPAHPSGIPQRKRSLIRPERNR 100
101 IGKDHPNYHYRKHAANMNTLPSSTGHDPIYEDLEGATDDVSGTGSRNDDD 150
151 VSEESPPRRKHSTKMQVIETEKSGDERRRRRKSDTTKHGKIVKASKGKRE 200
201 KSGGLPTPSFWNIYCGFVTFWCPGFVLKCFGMPEMAQQRAWREKMGLISI 250
251 ILLIMGFVGFITFGFTQVVCGKPPLRLRINEVGSGYMIFHGSAYDLTKSH 300
301 HPPAEGIPRRPDGLGANVIYDLPQHYGGQDGSFLFQNVNGKCKGLITKQE 350
351 NSDVPSDKSGNLAWYFPCNTFNQDGSSKPNTTIPYYLGYACHTTANARDS 400
401 FYLGLKSSADVYFTWDDIKNSSRNLVVYSGHVLDLDLLHWFNDTQVTYPA 450
451 RFKELRDKNTAGNQAIRGRDITHAFQSSKDKQIAECFEEIIKVGSVDTET 500
501 VGCIASKVVLYVSLVLILAVVLARFVLALIFQWFISKTYAAAKTSQTSDQ 550
551 RKRNRQIEDWTEDIYRAPPRLPGEVGSSVAGSSDRQSKRSSAFLPTHSRF 600
601 STVYGNERGNRKPGLPTTMASQNAAGQLLHPGTIYGQGNESRSSFLKSDA 650
651 YGSSSSPADGPGPAGFIHEAVVPQPPSDWMPFGFPLAHTICLVTAYSEGE 700
701 MGVRTTLDSIAMTDYPNSHKVILVICDGIIKGHGEEHSTPDIILGMMKDH 750
751 TIHPDDVEPFSYVAVATGSKRHNMAKVYTGFYDYGTNSAIPLEKQQRVPM 800
801 MMVVKCGTPAEASKSKPGNRGKRDSQIILMSFLQKVMFDERMTELEYEMF 850
851 NGLWKITGISPDFYEIVLMVDADTKVFPDSLTHMISAMVKDPEIMGLCGE 900
901 TKIANKRASWVSAIQVFEYFVSHHLAKAFESVFGGVTCLPGCFCMYRIKA 950
951 PKGAQNYWVPILANPDVVEHYSENVVDTLHKKNLLLLGEDRYLSTLMLRT 1000
1001 FPKRKQVFVPQAVCKTTVPDEFMVLLSQRRRWINSTIHNLMELVLVRDLC 1050
1051 GTFCFSMQFIVGIELIGTLVLPAAIAFTFYVVIISIINSPPQIIPLVLLG 1100
1101 LILGLPAILVVVTAHSWSYIIWMFIYLLSLPVWNFVLPTYAFWKFDDFSW 1150
1151 GDTRKTAGEKSSKGGHGEAEGEFDSSMITMKRWAEFERDRRVRSTYWAGS 1200
1201 RDNVISGVGGSNGWGSSQPRGHEQGRHFDDYFSDA 1235
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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