 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9TVM2 from www.uniprot.org...
The NucPred score for your sequence is 0.40 (see score help below)
1 MATMLTSDEAGKLLDFSQKLDINLLDKIVEVVYTAQGEQLRLAQSILTTL 50
51 KEHPEAWTRVDSILEYSQNQRTKFYALQILEEVIKTRWKVLPRNQCEGIK 100
101 KYVVSLIIKTSSDPIVMEQNKVYLNKLNMILVHILKREWPRNWETFISDI 150
151 VGASKTNESLCMNNMVILKNLSEEVFDFSQGQITQTKAKHLKDTMCSEFS 200
201 QIFTLCSFVLENSMNAALIHVTLETLLRFLNWIPLGYIFETQQIETLIFK 250
251 FLSVPMFRNVTLKCLSEIAGLTAANYDENFATLFKDTMVQLEQIVGQNMN 300
301 MNHVFKHGSDTEQELVLNLAMFLCTFLKEHGKLVEDAKYVDYLNQALMYL 350
351 VMISEVEDVEVFKICLEYWNSLVEDLYNSEFFHPTLESTKRQQVYPRRRF 400
401 YAPILSKVRFIMISRMAKPEEVLVVENENGEVVREFMKDTNSINLYKNMR 450
451 ETLVFLTHLDSVDTDRIMTLKLLNQVNGSEFSWKNLNTLCWAIGSISGAF 500
501 CEEDEKRFLVTVIKDLLGLCEQKKGKDNKAIIASNIMYVVGQYPRFLRAH 550
551 WKFLKTVVNKLFEFMHETHDGVQDMACDTFIKIAIKCRRYFVTIQPNEAC 600
601 TFIDEILTTMSSIICDLQPQQVHTFYEAVGYMISAQVDQVQQDVLIERYM 650
651 QLPNQVWDDIISRASKNVDFLKNMTAVKQLGSILKTNVAACKALGHAYVI 700
701 QLGRIYLDMLNVYKITSENIIQAIEVNGVNVNNQPLIKTMHVVKKETLNL 750
751 ISEWVSRSNDNQLVMDNFIPPLLDAILLDYQRCKVPSAREPKVLSAMAII 800
801 VHKLRQHITNEVPKIFDAVFECTLDMINKNFEDFPQHRLSFYELLQAVNA 850
851 HCFKAFLNIPPAQFKLVFDSVVWAFKHTMRNVADMGLNILFKMLQNLDQH 900
901 PGAAQSFYQTYFTDILMQIFSVVTDTSHTAGLPNHAIILAYMFSLVENRK 950
951 ITVNLGPIPDNMIFIQEYVASLLKSAFTHLSDNQVKVFVTGLFNLDENVQ 1000
1001 AFKEHLRDFLIQIREATGEDDSDLYLEEREAALAEEQSNKHQMQRNIPGM 1050
1051 LNPHELPEDMQDE 1063
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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