 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9ULL0 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MRAGWTPRGFSAFHASLLPGRHPYLAHLGPRDRGARIGSRAYSQGCCSCL 50
51 WLTYKGKKEGSTKGELGPAAVTDLEIPSYSRGFLPCTPRFPTTWCRGPGC 100
101 FCGTAVIAGNLGDLARIVGPSHHASQLLLLQEQDSGNHPTMAESLSEISD 150
151 SLDVLEAGDEGKKKCKFKALKSFFVKKKEKEAEDTQEEEMLELSLSSSNI 200
201 NISSLQPVRENQPTKARAKSSMGSKALSHDSIFMLGPEPERSASKMFPSM 250
251 DPQRGRPQQRSHISRTLPKPRSKVPGVVSGAMSGAVLQNVPTSAVWVAGP 300
301 KITENPPSRRRRLSIIPPVIQPEIISKNLVEISLDDESPKNPQKKALPHK 350
351 SLTATQSFSELSSGPDCSQSLTAFATLASTSSTQLPIGFSTPATTQGCLD 400
401 SSAARHKMTLNPRKQKKNLQVIIRGLPVWFSHFQGILEGSLQCVTQTLET 450
451 PNLDEPLPVEPKEEEPNLPLVSEEEKSITKPKEINEKKLGMDSADSSSQK 500
501 QNNKTEMYDKKTTDQAPNTDASRSQGYPMSAAYGRRWRRKGASVSGLSGC 550
551 EFKGRSLKQSSEGYGLGDRAGSSPTNKTARNVPFSHLSLEKDNMEQPTTS 600
601 QPETTTPQGLLSDKDDMGRRNAGIDFGSRKASAAQPIPENMDNSMVSDPQ 650
651 PYHEDAASGAEKTEARASLSLMVESLSTTQEEAILSVAAEAQVFMNPSHI 700
701 QLEDQEAFSFDLQKAQSKMESAQDVQTICKEKPSGNVHQTFTASVLGMTS 750
751 TTAKGDVYAKTLPPRSLFQSSRKPDAEEVSSDSENIPEEGDGSEELAHGH 800
801 SSQSLGKFEDEQEVFSESKSFVEDLSSSEEELDLRCLSQALEEPEDAEVF 850
851 TESSSYVEKYNTSDDCSSSEEDLPLRHPAQALGKPKNQQEVSSASNNTPE 900
901 EQNDFMQQLPSRCPSQPIMNPTVQQQVPTSSVGTSIKQSDSVEPIPPRHP 950
951 FQPWVNPKVEQEVSSSPKSMAVEESISMKPLPPKLLCQPLMNPKVQQNMF 1000
1001 SGSEDIAVERVISVEPLLPRYSPQSLTDPQIRQISESTAVEEGTYVEPLP 1050
1051 PRCLSQPSERPKFLDSMSTSAEWSSPVAPTPSKYTSPPWVTPKFEELYQL 1100
1101 SAHPESTTVEEDISKEQLLPRHLSQLTVGNKVQQLSSNFERAAIEADISG 1150
1151 SPLPPQYATQFLKRSKVQEMTSRLEKMAVEGTSNKSPIPRRPTQSFVKFM 1200
1201 AQQIFSESSALKRGSDVAPLPPNLPSKSLSKPEVKHQVFSDSGSANPKGG 1250
1251 ISSKMLPMKHPLQSLGRPEDPQKVFSYSERAPGKCSSFKEQLSPRQLSQA 1300
1301 LRKPEYEQKVSPVSASSPKEWRNSKKQLPPKHSSQASDRSKFQPQMSSKG 1350
1351 PVNVPVKQSSGEKHLPSSSPFQQQVHSSSVNAAARRSVFESNSDNWFLGR 1400
1401 DEAFAIKTKKFSQGSKNPIKSIPAPATKPGKFTIAPVRQTSTSGGIYSKK 1450
1451 EDLESGDGNNNQHANLSNQDDVEKLFGVRLKRAPPSQKYKSEKQDNFTQL 1500
1501 ASVPSGPISSSVGRGHKIRSTSQGLLDAAGNLTKISYVADKQQSRPKSES 1550
1551 MAKKQPACKTPGKPAGQQSDYAVSEPVWITMAKQKQKSFKAHISVKELKT 1600
1601 KSNAGADAETKEPKYEGAGSANENQPKKMFTSSVHKQEKTAQMKPPKPTK 1650
1651 SVGFEAQKILQVPAMEKETKRSSTLPAKFQNPVEPIEPVWFSLARKKAKA 1700
1701 WSHMAEITQ 1709
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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