 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VJB6 from www.uniprot.org...
The NucPred score for your sequence is 0.61 (see score help below)
1 MVDPLKIFWVLTNSTYLVTKFVRIGIADKNDSPPYFDRFLYETEIDENAD 50
51 LQSTVLTVNAKDHNESTNIRYQITGGNIGNAFAVQNTTGVIYVASPLDYE 100
101 TRPRYELRLEATRNRKNNYTTVVINVRDVNDNPPVFDRQTYRTQITEEDD 150
151 RNLPKRILQVTATDGDVDRPINIVYFLTGQGIDPDNPANSKFDINRTTGD 200
201 IFVLKPLDRDQPNGRPQWRFTVFAQDEGGEGLVGYADIQVNLKDINDNAP 250
251 QFPQGIYFGNVTENGTAGSSVMTMSAVDYDDPNESTNAKLIYSIEKNVIE 300
301 EETGAPIFEIEPETGLIKTAVCCLDRERTPDYSIQVVAMDGGGLKGTGTA 350
351 SIRVKDLNDMPPQFTKDEWVTEVDETNGTYIPETPILTVTVQDEDETNTF 400
401 QYKVVPNSGFGADKFAMVRNGDGTGSLKIIQPLDYEDPLQSSGFRFRIQV 450
451 NDKGDDGPGGSDKYHVAYSWVVVKLRDINDNVPKFDREHIEVSIYEDTKV 500
501 GTILEQFKATDADQGGHSKVAYKIVRSTNRKRQFAISDRGAVSIQRPLDR 550
551 ETQDRHHIQILAIDDGSPARTATATLTVIVKDVNDNAPTFAQDYKPTLPE 600
601 NVSGKKILEVAAKDPDDRLRGNGGPFTFRLDPLASDEIKAGFKVEYDRRG 650
651 DNENGVAIISSLRPFDREAQKSYAIPIEIKDNGAPAMTGTSTLTVTIGDV 700
701 NDNKMQPGSKSVLVYNYQGQSQDTPIGRVYVNDPDDWDVPDKKYYWEVQE 750
751 HQRFKLDTDTGILTMRAGTRRGRYQLRFKVYDREHGQEDIPANLSVTVRD 800
801 ITAEAVQQAGSMRLSHITDEDFVRTWNPVKNQVEPSKLERFRNKLAELLY 850
851 TDRDNVDVFSVQLKEGSPYPLTDVHFAARSATQQPYFKAVRLNGVVQMHR 900
901 EEIEKDVGLNITMVNINECLHEGKGKCGSNSCTSKVELGKKPYTVSVNRT 950
951 ALVGVRLDISAQCVCRARNFTHQDHNCRTHLCYNGGRCVETRNGPKCVAC 1000
1001 PVGYNGPRCQQSTRSFRGNGWAWYPPLQLCQESHLSLEFITRVADGLILY 1050
1051 NGPIVPPKPEETVISDFIALELEQGYPRLLIDFGSGTLELRVKTKKTLDD 1100
1101 GVWHRLDIFWDTENVRMVVDFCRTALVSEMEDGTPPEFDDNACQARGQIP 1150
1151 PFAESLNLNQPLQLGGLYRQHFDQTLYNWQYAFSSKGFDGCIRNVIHNSE 1200
1201 HYDLAFPALARNSFPACPQTDEVCLKTEHTARCWEHGNCVASLVQAKCHC 1250
1251 QPGWMGPGCNVPTIPTTFKAQSYVKFALSFEPDRFSTQLQLRFRTREQGG 1300
1301 ELFRVSDQHHREYAILELRRGHLQFRYNLNSMRNEEQLLTLTAIAVNDGQ 1350
1351 WHVIRISRYGSAALMELDGGESRRYNESFHFTGHQWLTIDKQEGVYAGGK 1400
1401 AEYTGIKTFEVQSDFQRSCLDDIRLDGKHLPLPPAMNGTQWGQATMARNL 1450
1451 ERNCPSNRPCSNVICPDPFDCVDLWNEYECTCSEGRIMSSDTKGCVDRNE 1500
1501 CLDLPCLNGATCINLEPRLRYRCICPEGYWGENCELVQEGQRLKLSMGAL 1550
1551 GAIFVCLIIILILALIFVLYSRKRKTTKKKKRSGPEKDVRETVISYEDEG 1600
1601 GGEDDMTAFDITPLQIPISAQGGPPDIAACKMPIIYPVMTLLPPGQELNV 1650
1651 AYLMEERKQRIDKDNNAPPFDDLRNFTFEGSGSIAESLSSLASGTDDENQ 1700
1701 DFNYLQNWGPRFNALAAMYVHDKAKASSQLPSDGGGGSGDGPGPGASSSS 1750
1751 PLGGGGTGGGSGIPGNVLAVVATGSGAGPGGGGGSSGLMPLPEVDKVVL 1799
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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