| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7Z3B3 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MAAMAPALTDAAAEAHHIRFKLAPPSSTLSPGSAENNGNANILIAANGTK 50
51 RKAIAAEDPSLDFRNNPTKEDLGKLQPLVASYLCSDVTSVPSKESLKLQG 100
101 VFSKQTVLKSHPLLSQSYELRAELLGRQPVLEFSLENLRTMNTSGQTALP 150
151 QAPVNGLAKKLTKSSTHSDHDNSTSLNGGKRALTSSALHGGEMGGSESGD 200
201 LKGGMTNCTLPHRSLDVEHTTLYSNNSTANKSSVNSMEQPALQGSSRLSP 250
251 GTDSSSNLGGVKLEGKKSPLSSILFSALDSDTRITALLRRQADIESRARR 300
301 LQKRLQVVQAKQVERHIQHQLGGFLEKTLSKLPNLESLRPRSQLMLTRKA 350
351 EAALRKAASETTTSEGLSNFLKSNSISEELERFTASGIANLRCSEQAFDS 400
401 DVTDSSSGGESDIEEEELTRADPEQRHVPLRRRSEWKWAADRAAIVSRWN 450
451 WLQAHVSDLEYRIRQQTDIYKQIRANKGLIVLGEVPPPEHTTDLFLPLSS 500
501 EVKTDHGTDKLIESVSQPLENHGAPIIGHISESLSTKSCGALRPVNGVIN 550
551 TLQPVLADHIPGDSSDAEEQLHKKQRLNLVSSSSDGTCVAARTRPVLSCK 600
601 KRRLVRPNSIVPLSKKVHRNSTIRPGCDVNPSCALCGSGSINTMPPEIHY 650
651 EAPLLERLSQLDSCVHPVLAFPDDVPTSLHFQSMLKSQWQNKPFDKIKPP 700
701 KKLSLKHRAPMPGSLPDSARKDRHKLVSSFLTTAKLSHHQTRPDRTHRQH 750
751 LDDVGAVPMVERVTAPKAERLLNPPPPVHDPNHSKMRLRDHSSERSEVLK 800
801 HHTDMSSSSYLAATHHPPHSPLVRQLSTSSDSPAPASSSSQVTASTSQQP 850
851 VRRRRGESSFDINNIVIPMSVAATTRVEKLQYKEILTPSWREVDLQSLKG 900
901 SPDEENEEIEDLSDAAFAALHAKCEEMERARWLWTTSVPPQRRGSRSYRS 950
951 SDGRTTPQLGSANPSTPQPASPDVSSSHSLSEYSHGQSPRSPISPELHSA 1000
1001 PLTPVARDTPRHLASEDTRCSTPELGLDEQSVQPWERRTFPLAHSPQAEC 1050
1051 EDQLDAQERAARCTRRTSGSKTGRETEAAPTSPPIVPLKSRHLVAAATAQ 1100
1101 RPTHR 1105
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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