| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O77448 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MQKINNINNNKQMLTRKEDLLTVLKQISALKYVSNLYEFLLATEKIVQTS 50
51 ELDTQFQEFLTTTIIASEQNLVENYKQKYNQPNFSQLTIKQVIDDSIILL 100
101 GNKQNYVQQIGTTTIGFYVEYENINLSRQTLYSSNFRNLLNIFGEEDFKY 150
151 FLIDFLVFTKVEQNGYLQVAGVCLNQYFSVQVKQKKWYKNNFNMNGKATS 200
201 NNNQNNANLSNEKKQENQYIYPEIQRSQIFYCNHMGREPGVFKSSFFNYS 250
251 EIKKGFQFKVIQEKLQGRQFINSDKIKPDHPQTIIKKTLLKEYQSKNFSC 300
301 QEERDLFLEFTEKIVQNFHNINFNYLLKKFCKLPENYQSLKSQVKQIVQS 350
351 ENKANQQSCENLFNSLYDTEISYKQITNFLRQIIQNCVPNQLLGKKNFKV 400
401 FLEKLYEFVQMKRFENQKVLDYICFMDVFDVEWFVDLKNQKFTQKRKYIS 450
451 DKRKILGDLIVFIINKIVIPVLRYNFYITEKHKEGSQIFYYRKPIWKLVS 500
501 KLTIVKLEEENLEKVEEKLIPEDSFQKYPQGKLRIIPKKGSFRPIMTFLR 550
551 KDKQKNIKLNLNQILMDSQLVFRNLKDMLGQKIGYSVFDNKQISEKFAQF 600
601 IEKWKNKGRPQLYYVTLDIKKCYDSIDQMKLLNFFNQSDLIQDTYFINKY 650
651 LLFQRNKRPLLQIQQTNNLNSAMEIEEEKINKKPFKMDNINFPYYFNLKE 700
701 RQIAYSLYDDDDQILQKGFKEIQSDDRPFIVINQDKPRCITKDIIHNHLK 750
751 HISQYNVISFNKVKFRQKRGIPQGLNISGVLCSFYFGKLEEEYTQFLKNA 800
801 EQVNGSINLLMRLTDDYLFISDSQQNALNLIVQLQNCANNNGFMFNDQKI 850
851 TTNFQFPQEDYNLEHFKISVQNECQWIGKSIDMNTLEIKSIQKQTQQEIN 900
901 QTINVAISIKNLKSQLKNKLRSLFLNQLIDYFNPNINSFEGLCRQLYHHS 950
951 KATVMKFYPFMTKLFQIDLKKSKQYSVQYGKENTNENFLKDILYYTVEDV 1000
1001 CKILCYLQFEDEINSNIKEIFKNLYSWIMWDIIVSYLKKKKQFKGYLNKL 1050
1051 LQKIRKSRFFYLKEGCKSLQLILSQQKYQLNKKELEAIEFIDLNNLIQDI 1100
1101 KTLIPKISAKSNQQNTN 1117
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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