 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P78621 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MPTSDKSRQTSAGKSFFGRKLHKERPVEDRWDAHGSWESLAPPSSAAGSR 50
51 SSRYSKRSSIQSVDFGADIDPSLLSTSAGPITSIPFESLSTDTQSPIPVD 100
101 YLSKAETSPRKEPSPGHLAKGVGDFHQYPAWDPSAMRNHQQFSHPTGPRP 150
151 PPHAAGVAMSSSATGDKGARYQQWGRPGSSAGNAGLSHHSSSTVDSSTNS 200
201 RMSIDQASIHSSLSSNTRGSSYISTDGSSRTTLPSHSNDRSNYYAAMNSG 250
251 RGSSAQGAIPPAQPRVQNTEQYLTRPRDDRVVDQLFLELMQKRGWQNLPE 300
301 QARRQMMAYPASKKWTLVHQDRLTELQGEQKRKQKARETHGYDGPSGILE 350
351 RADEEGSPEWYVKKVMDDTITSKQLASLSVSLRTQPISWVKAFVEAQGQI 400
401 ALTNVLVKINRKKVTGPVPAPPSGDKDLDREYDIVKCLKALMNNKYGADD 450
451 ALAHQQIIVALISSLLSPRLNTRKLVSEVLTFLCHWAEGQGHERVLQAMD 500
501 HVKNHQGETGRFDAWMRIVEVTIDGRGKMGSLVGASEEYRSGGIGMENLL 550
551 MEYAVSTMILINMLVDAPENDLQLRCHIRAQFISCGIKRLLSKMEGFQYE 600
601 VIDKQIEHFRENEAIDYEDLLQRESSSTKDSIEGEVKDMTDPLQITDAIA 650
651 SRLNGTRAHDYFLSALQHLLLIRENSGEDGLRMYQLVDAMLSYVAMDRRL 700
701 PDLDLRQGLTFTVQSLLDRLHTDAEARRAYDESLEARQIAEAALAERDEM 750
751 KAQVELGADGLVRKLQKQIEEQTGIIELQSRQNEMLKAELADVQRLRAQE 800
801 LQRNELETRELYLMLRDAQDIAASNAKKSNMGEAETDPAHMRGILDREKL 850
851 LTRLEKQLERTKTQFKLEGKVWGQHDPSDRLRELREQMDGDAGPREAFEE 900
901 QARLNLSLNPVGSVYRKKTYIQGMEDTATEELGQTDDEVVYAKARLVDLH 950
951 RPRMDPEQATGLLGEIAAKVPKIDADDAKDEGKPTESEQPAEGAATKGDE 1000
1001 QGVDDTVAVDKATAAPPPPPPPPPAHPGLSGAAPPPPPPPPPPPPGAGAA 1050
1051 PPPPPPPPPPPPGGLGGPPPPPPPPPPGGFGGPPPPPPPPGGFGGPPPPP 1100
1101 PPPPGGAFGVPPPPPPPGTVIGGWRANYLASQGAPSHAIPVMSSIRPKKK 1150
1151 LKALHWDKVDTPQVTVWATHGTTPQEKEEKYVELAKRGVLDEVERLFMAK 1200
1201 ETRIFGGGVAAKQRKDKKQIISNDLSKNFQIALSKFSQFPAEEVVRRIIH 1250
1251 CDAEILDNMVVMEFLQRDEMCTVPENVSKLMAPYSKDWTGPDAANTEREQ 1300
1301 DPSELTREDQIYLYTAFELNHYWKARMRALALTRSFEPDYEHISAKLREV 1350
1351 VRVSESLRDSVSLMNVLGLILDIGNFMNDANKQAQGFKLSSLARLGMVKD 1400
1401 DKNETTFADLVERIVRNQYPEWEDFTEQISGVIGLQKLNVDQLRTDAKKY 1450
1451 IDNIKNVQASLDAGNLSDPKKFHPQDRVSQITQRSMKDARRKAEQMQLYL 1500
1501 EEMVKTYDDIMVFYGEDNTDDGARRDFFAKLAAFLQEWKKSKEKNIALEE 1550
1551 ARRRTEASLARKRINVGLANGAGAAGDAPVSPATSGAMDSLLEKLRAAAP 1600
1601 QAKDQRDRRRRARLKERHQVRVASGQKIPDLEGAEAPGSGGQNSGATDTN 1650
1651 ATDSSLLSPTIQEPEGGSSPIASQSEDVADRAASMLQDMLRNSPDPERTR 1700
1701 RRRESAEEERRKRRLRRRNGATSGSKDSNDTTPLSPVTEPTSTQGESAEP 1750
1751 ENLSLSSPPNGEDPTLNPPTIVLSSDASDTPDDEHRPSTS 1790
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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