| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P24339 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MAPRVAPGGSQQFLGKQGLKAKNPVSTPNSHFRSASNPRKRREPPTIDTG 50
51 YPDRSDTNSPTDHALHDENETNINVVVRVRGRTDQEVRDNSSLAVSTSGA 100
101 MGAELAIQSDPSSMLVTKTYAFDKVFGPEADQLMLFENSVAPMLEQVLNG 150
151 YNCTIFAYGQTGTGKTYTMSGDLSDSDGILSEGAGLIPRALYQLFSSLDN 200
201 SNQEYAVKCSYYELYNEEIRDLLVSEELRKPARVFEDTSRRGNVVITGIE 250
251 ESYIKNAGDGLRLLREGSHRRQVAATKCNDLSSRSHSIFTITLHRKVSSG 300
301 MTDETNSLTINNNSDDLLRASKLHMVDLAGSENIGRSGAENKRARETGMI 350
351 NQSLLTLGRVINALVEKAHHIPYRESKLTRLLQDSLGGKTKTSMIVTVSS 400
401 TNTNLEETISTLEYAARAKSIRNKPQNNQLVFRKVLIKDLVLDIERLKND 450
451 LNATRKKNGVYLAESTYKELMDRVQNKDLLCQEQARKLEVLDLNVKSSRE 500
501 QLQYVSKSNQEHKKEVEALQLQLVNSSTELESVKSENEKLKNELVLEIEK 550
551 RKKYETNEAKITTVATDLSQYYRESKEYIASLYEKLDRTERNNKENENNF 600
601 WNLKFNLLTMLRSFHGSFTDETNGYFTLLNDFNASMEELLNTHSNQLLIS 650
651 MTKITEHFQSLDEALQSARSSCAVPNSSLDLIVSELKDSKNSLLDALEHS 700
701 LQDISMSSQKLGNGISSELIELQKDMKESYRQLVQELRSLYNLQHTHEES 750
751 QKELMYGVRNDIDALVKTCTTSLNDADIILSDYISDQKSKFESKQQDLIA 800
801 NIGKIVSNFLQEQNESLYTKADILHSHLNDTNSNIRKANEIMNNRSEEFL 850
851 RNAASQAEIVGANKERIQKTVENGSQLLDSKSKAIHSNSRSMYDHCLALA 900
901 ESQKQGVNLEVQTLDRLLQKVKEHSEDNTKEKHQQLLDLLESLVGNNDNL 950
951 IDSIKTPHTELQKITDHVLKGTTSLANHTNELLGLGDESLCNLETTIEDT 1000
1001 SLVKLETTGDTPSKRELPATPSWTRDSSLIKETTNLNLDSDKKFVRETYT 1050
1051 SSNQTNEPDVYDKPSNSSRTSLLRSSRSAYSKMKR 1085
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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