 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q69ZB8 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MLRMKLPPKSTHPSEPPPDAEEPEADARPGAKAPLRRRRDCRPPPPPTGL 50
51 PRGPPPPPSPPRGLEPPVASGPTAGAGMPGGGGHAAALREQERVYEWFGL 100
101 VLGSAQRLEFMCGLLDLCNPLELRFLGSCLEDLARKDYHYLRDSEAKANG 150
151 LSDPGSLADFREPAVRSRLIVYLALLGSENREAAGRLHRLLPQVDAVLRS 200
201 LRATRAEGSRGSVEDEPSGDGEQDAEKDGPGPEGSGCAKLGTGGGLGFRA 250
251 QEELLLLFTMASLHPAFSFHQRVTLREHLERLRSALRVEPEDAEVEPSNF 300
301 AGSRAQNDSACGDYIQSNETGLVEQAQIPPDGLTVAPHRAQREAVHIEKI 350
351 MLKGVQRKRADKYWEYTFKVNWSDLSVTTVTKTHQELQEFLLKLPKEFSS 400
401 ESFDKTILKALNQGSLRREERRHPDLEPILRQLFSTSPQAFLQSHKVRSF 450
451 FRSISSESQHNFNNLQSSLKTSKILEHLKEDSSEASSQEEDVLQHTIIHK 500
501 KHAGKSPALNVATSCSPLDGLTMQYAEQNGIVDWRNQGCAAIQHSEHCVS 550
551 SADQHSAEKRSLSSGNKKKGKPQVEKEKVKKTEDRLNSRINGIRLSAPQH 600
601 VHGSTVKDMNLDIGSGHDTCGETSSESYSSPSSPRHDGRESLESEEEKDR 650
651 DSDSNSEDSVNPSSARFSGYGSVAQTIAVKPPAETVSLGTEDGNLLEAAL 700
701 TSHKYPHIPFMPTLHCVTHNGAQKSQVVIPSPKSADGKTLGMLVPNAVAI 750
751 SAVMESSNSAPVGILGPAASGESEKHLELLASPLPLPSTFLPHSSAPALQ 800
801 LTLQSLKLQPPQGSSDSCPVSIPPQPTGSLSIGSPNTAFIPVHNPGSFPG 850
851 SPVATTDPITKSAPQVVGLNQMVPQIEGNTGTVPQPSNVKVVLPAAGLSA 900
901 AQPPASFPFPGSPQAASALPTQNSSALNAATSAQPASTGISPSQSTVPPA 950
951 VPTHTPGPAPSPSPALTHSTAQSDSTSYISAVGNTNANGTIVPPQQMGPC 1000
1001 GSCGRRCSCGTNGNLQLNSYYYPNPMPGPMYRLPSFFTLPSICNGSYLNQ 1050
1051 AHQSNGNQLPFFLPQTPYANGLVHDPVMGSQASYGMQQMAGFGRLYPVYP 1100
1101 APNVVANTSGSGPKKNGNVSCYNCGVSGHYAQDCKQSSMEANQQGTYRLR 1150
1151 YAPPLPPSNDTLDSAD 1166
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.) |
Go back to the NucPred Home Page.