 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O60437 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MNSLFRKRNKGKYSPTVQTRSISNKELSELIEQLQKNADQVEKNIVDTEA 50
51 KMQSDLARLQEGRQPEHRDVTLQKVLDSEKLLYVLEADAAIAKHMKHPQG 100
101 DMIAEDIRQLKERVTNLRGKHKQIYRLAVKEVDPQVNWAALVEEKLDKLN 150
151 NQSFGTDLPLVDHQVEEHNIFHNEVKAIGPHLAKDGDKEQNSELRAKYQK 200
201 LLAASQARQQHLSSLQDYMQRCTNELYWLDQQAKGRMQYDWSDRNLDYPS 250
251 RRRQYENFINRNLEAKEERINKLHSEGDQLLAAEHPGRNSIEAHMEAVHA 300
301 DWKEYLNLLICEESHLKYMEDYHQFHEDVKDAQELLRKVDSDLNQKYGPD 350
351 FKDRYQIELLLRELDDQEKVLDKYEDVVQGLQKRGQQVVPLKYRRETPLK 400
401 PIPVEALCDFEGEQGLISRGYSYTLQKNNGESWELMDSAGNKLIAPAVCF 450
451 VIPPTDPEALALADSLGSQYRSVRQKAAGSKRTLQQRYEVLKTENPGDAS 500
501 DLQGRQLLAGLDKVASDLDRQEKAITGILRPPLEQGRAVQDSAERAKDLK 550
551 NITNELLRIEPEKTRSTAEGEAFIQALPGSGTTPLLRTRVEDTNRKYEHL 600
601 LQLLDLAQEKVDVANRLEKSLQQSWELLATHENHLNQDDTVPESSRVLDS 650
651 KGQELAAMACELQAQKSLLGEVEQNLQAAKQCSSTLASRFQEHCPDLERQ 700
701 EAEVHKLGQRFNNLRQQVERRAQSLQSAKAAYEHFHRGHDHVLQFLVSIP 750
751 SYEPQETDSLSQMETKLKNQKNLLDEIASREQEVQKICANSQQYQQAVKD 800
801 YELEAEKLRSLLDLENGRRSHVSKRARLQSPATKVKEEEAALAAKFTEVY 850
851 AINRQRLQNLEFALNLLRQQPEVEVTHETLQRNRPDSGVEEAWKIRKELD 900
901 EETERRRQLENEVKSTQEEIWTLRNQGPQESVVRKEVLKKVPDPVLEESF 950
951 QQLQRTLAEEQHKNQLLQEELEALQLQLRALEQETRDGGQEYVVKEVLRI 1000
1001 EPDRAQADEVLQLREELEALRRQKGAREAEVLLLQQRVAALAEEKSRAQE 1050
1051 KVTEKEVVKLQNDPQLEAEYQQLQEDHQRQDQLREKQEEELSFLQDKLKR 1100
1101 LEKERAMAEGKITVKEVLKVEKDAATEREVSDLTRQYEDEAAKARASQRE 1150
1151 KTELLRKIWALEEENAKVVVQEKVREIVRPDPKAESEVANLRLELVEQER 1200
1201 KYRGAEEQLRSYQSELEALRRRGPQVEVKEVTKEVIKYKTDPEMEKELQR 1250
1251 LREEIVDKTRLIERCDLEIYQLKKEIQALKDTKPQVQTKEVVQEILQFQE 1300
1301 DPQTKEEVASLRAKLSEEQKKQVDLERERASQEEQIARKEEELSRVKERV 1350
1351 VQQEVVRYEEEPGLRAEASAFAESIDVELRQIDKLRAELRRLQRRRTELE 1400
1401 RQLEELERERQARREAEREVQRLQQRLAALEQEEAEAREKVTHTQKVVLQ 1450
1451 QDPQQAREHALLRLQLEEEQHRRQLLEGELETLRRKLAALEKAEVKEKVV 1500
1501 LSESVQVEKGDTEQEIQRLKSSLEEESRSKRELDVEVSRLEARLSELEFH 1550
1551 NSKSSKELDFLREENHKLQLERQNLQLETRRLQSEINMAATETRDLRNMT 1600
1601 VADSGTNHDSRLWSLERELDDLKRLSKDKDLEIDELQKRLGSVAVKREQR 1650
1651 ENHLRRSIVVIHPDTGRELSPEEAHRAGLIDWNMFVKLRSQECDWEEISV 1700
1701 KGPNGESSVIHDRKSGKKFSIEEALQSGRLTPAQYDRYVNKDMSIQELAV 1750
1751 LVSGQK 1756
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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