 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P14068 from www.uniprot.org...
The NucPred score for your sequence is 0.41 (see score help below)
1 MEGILAFDRELDVALLDRVVQTFYQGVGAEQQQAQQVLTQFQAHPDAWSQ 50
51 AYSILEKSEYPQTKYIALSVLDKLITTRWKMLPKEQRLGIRNYIVAVMIK 100
101 NSSDETVLQQQKTFLNKLDLTLVQILKQEWPHNWPNFIPEIVQASKTNLS 150
151 LCENNMIVLRLLSEEIFDYSAEQMTQLKTKNLKNQMCGEFAEIFQLCSQI 200
201 LERAQKPSLIKATLGTLLRFLNWIPLGYIFETNIVELITNRFLNVPDFRN 250
251 VTIECLTEIASLTSQPQYNDKFVTMFNLVMTSVNSMLPLQTDFREAYEES 300
301 STNEQDFIQNLALFLCAFFSSHLRPLENPENQEVLLNAHSYLLNISRINE 350
351 REIFKICLEYWSKLVAQLYEEMQQIPMSEMNPLLNLSSPTSLISSNPNML 400
401 ANLPLRKHIYKDILSTLRLVMIENMVKPEEVLIVENDEGEIVREFVKETD 450
451 TITLYKSMREVLVYLTHLDVVDTEIVMTEKLARIVVGTEWSWQNLNTLCW 500
501 AIGSISGAMNEEMEKRFLVNVIKDLLGLCEMKRGKDNKAVVASNIMYVVG 550
551 QYPRFLKAHWKFLKTVVNKLFEFMHEYHEGVQDMACDTFIKIAQKCRRHF 600
601 VAQQLGETEPFINEIIRNLAKTTEDLTPQQTHTFYEACGYMISAQPQKHL 650
651 QERLIFDLMALPNQAWENIVAQAAQNAQVLGDPQTVKILANVLKTNVAAC 700
701 TSIGSGFYPQIAKNYVDMLGLYKAVSGLISEVVAAQGNIATKTPHVRGLR 750
751 TIKKEILKLVDAYISRAEDLELVGNTLIPALFEAVLLDYLQNVPDARDAE 800
801 VLNLITTIVNQLSELLTDKIPLVLDAVFGCTLEMISKDFSEYPEHRAAFF 850
851 QLLRAINLNCFPALLNIPAPQFKLVINSIVWSFKHVSRDIQETGLNILLE 900
901 LINNMASMGPDVSNAFFQTYYISLLQDILYVLTDSDHKSGFKLQSLILAR 950
951 LFYLVESNQITVPLYDPSQFPQEMNNQLFLRQYIMNLLVTAFPHLQPIQI 1000
1001 QEFVQTVLALNQDSIKFKLALRDFLIQLKEFGGDNAELYLEEKEQELAAQ 1050
1051 QKAQLEKAMTVPGMIKPVDMPTMEEEEL 1078
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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