| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O54931 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MAEAELHKERLQAIAEKRKRQTEIEGKRRQLDEQVLLLQHSKSKVLREKW 50
51 LLQGVPAGTAEEEEARRRQSEEDEFKVKQLEDNIQRLEQEIQALESEESQ 100
101 ISAKEQIILEKLKETEKSFKDLQKSFSTADGASGWSTVLLQGDELTADPI 150
151 GTNADMAIQKPPQLSEDANQLRSKQDNCGDSRLEPAASSLSPDHKNMEIG 200
201 VSVAECKSVPGVTSTPHSKDHSSPFYSPSHNGLLADHHESLDNDVAREIQ 250
251 YLDEVLEANCCDSSVDGTYNGISSPEPGAAILVSSLGSPAHSVTEAEPTE 300
301 KASGRQVPPHIELSRSPSDRMAEGERANGHSTDQPQDLLGNSLQAPASPS 350
351 SSTSSHCSSRDGEFTLTTLKKEAKFELRAFHEDKKPSKLFEEDEREKEQF 400
401 CVRKVRPSEEMIELEKERRELIRSQAVKKNPGIAAKWWNPPQEKTIEEQL 450
451 DEEHLESHRKYKERKEKRAQQEQLQLQQQQQQQLQQQQLQQQQLQQQQLQ 500
501 QQLQQQQLSTSQPCTAPAAHKHLDGIEHTKEDVVTEQIDFSAARKQFQLM 550
551 ENSRQTLAKGQSTPRLFSIKPYYKPLGSIHSDKPPTILRPATVGGTLEDG 600
601 GTQAAKEQKAPCVSESQSAGAGPANAATQGKEGPYSEPSKRGPLSKLWAE 650
651 DGEFTSARAVLTVVKDEDHGILDQFSRSVNVSLTQEELDSGLDELSVRSQ 700
701 DTTVLETLSNDFSMDNISDSGASNETPSALQENSLADFSLPQTPQTDNPS 750
751 EGREGVSKSFSDHGFYSPSSTLGDSPSVDDPLEYQAGLLVQNAIQQAIAE 800
801 QVDKAEAHTSKEGSEQQEPEATVEEAGSQTPGSEKPQGMFAPPQVSSPVQ 850
851 EKRDILPKNLPAEDRALREKGPSQPPTAAQPSGPVNMEETRPEGGYFSKY 900
901 SEAAELRSTASLLATQESDVMVGPFKLRSRKQRTLSMIEEEIRAAQEREE 950
951 ELKRQRQVRQSTPSPRAKNAPSLPSRTTCYKTAPGKIEKVKPPPSPTTEG 1000
1001 PSLQPDLAPEEAAGTQRPKNLMQTLMEDYETHKSKRRERMDDSSYTSKLL 1050
1051 SCKVTSEVLEATRVNRRKSALALRWEAGIYANQEEEDNE 1089
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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