 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8VXP3 from www.uniprot.org...
The NucPred score for your sequence is 0.45 (see score help below)
1 MLPLEHKASGRVQATGRGVRASVELSSVLPQQRAAQLQHQKCNTGARLGR 50
51 DPRRGVDAERTLVCTAATTASVPSTSGASPSGSQLSSKALRPRRFSAPVI 100
101 ARLLRSTTTVQELADLVQQQSLYMDSSHVGIAMLHLALLVSRAEQQAAAQ 150
151 LQLQLAAKQAATRRAGSGASTSGRARGWGSGPGRNGSGSSSVSVNGSGSS 200
201 SNGSSSSSSSLAMGMQLSMASIGDDVVSGVNAGPVPSGGADALLDLEMSS 250
251 ILDDDDGAGARQLQQMSDDLAAGLEAAATTTAAPEAGVAAAGGTGAGAAA 300
301 DAAASSSAPSLVAAAAAAAAAAASPASSPDVARTLRTLLSRAFSLGLDSL 350
351 SGPQLAAVFTGLAVLRRPRQQQQQQQQAGAAGAGANAGAGGVGGVGVSAG 400
401 DRLVAEQLLAAMGPKLYECRPQDLANTLASVALLGLPPDADLRTSFYAAV 450
451 RQQQRRFGPRELATTLWAYGAMGTYVQEDAVQLVLELSRARLTSFSPLQL 500
501 AKAVQGLAALRYRPSPEWVEAYCSVLRPALRRMSSRELCAVLLALASLQV 550
551 GLDGGTRAALLVHTFSGPLPGMAPGEVALSLWALGRLSAVDMDLPALIDL 600
601 DMSGRVLDLTSRLLAAGGFSGGELQQLLEGLTRLALQPPLEWMQAFVAAL 650
651 QPQLDKLDAQQLAGVLNSLAAQQYRPQPQMQEVVLAATQANMKQLLADTT 700
701 CSAALLTALRRLNIEPPPGWVGALLEESRSALKNRCTDLHLANLAGSLAA 750
751 WGVRPDGRWAARLMWRSQVLMNEDRMSPRALVALLQAMVSLGLSPNPVWT 800
801 QLCLQAAVRRASQPAFEPHHYGTLMASLHALGIQPPQEWLTRMLLSTYRC 850
851 WDRFSVTHWSSLLPALVLLKARPPREWLRRFEATSAARLADCSALQLLTL 900
901 AVSLAQLHQLHAAGAVADTPLLLPGAAAAAAAAAPAGASSAAAAGDSPAA 950
951 LSAVPAAAGDGALVPSFMSIDDDGTAAVAAAATALAAAEPAAHAATSTTT 1000
1001 ATAVAHPQPQLLPQAQALPQPGPEWQAAWWAASTRLLLRVRYAPSELVLT 1050
1051 AGWLGSLGLRPPPEWLQACAEVAARYSKVMDAAERQQLAAAVAPLALEAV 1100
1101 APPSAPPAGAASTAH 1115
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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