 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P83038 from www.uniprot.org...
The NucPred score for your sequence is 0.77 (see score help below)
1 MSSQSHPDGLSGRDQPVELLNPPRVNHMPSSVDVSTALPLQVAPTSVPMD 50
51 LRLDHQFPMPVTEPTLREQQLQQELLALKQKQQIQRQILIAEFQRQHEQL 100
101 SRQHEAQLHEHIKQQEMLAMKHQQELLEHQRKLEQHRQEQELEKQHREQK 150
151 LQQLKNKEKGKESAVASTEVKMKLQEFVLNKKKALAHRNLNHCISSDPRF 200
201 WYGKTQHSSLDQSSPPQSGVSGTYNHPVLGMYDSKDDFPLRKTASEPNLK 250
251 LRSRLKQKVAERRSSPLLRRKDGPVVTALKKRPLDVTDSACNSAPGSGPS 300
301 SPNNSSNNISAENGITGSVTSIQAETSLAHRLVNREGSVTQLPLYTSPSL 350
351 PNITLGLPATGPSSGGSAQQDAERLAIPALQQRISLFPGTHLTPYLSTTT 400
401 LERDGGTAHNPLLQHMVLLEQPTAQTPLVTGLPLHAQSLVGGERVSPSIH 450
451 KLRQHRPLGRTQSAPLPQNAQALQQLVIQQQHQQFLEKHKQQFQQQQLHI 500
501 NKIISKPNEPARQHESHPEETEEELREHQALLEEPYSDRVSSQKEVPGLA 550
551 NMVQVKQEPIESDEEEAEPQQELESGQRQAEQELLFRQQALLLEQQRIHQ 600
601 LRNYQASLEAAGMPVSFGGHRPLSRAQSSPASATFPMSVQEPPTKPRFTT 650
651 GLVYDTLMLKHQCTCGNTNSHPEHAGRIQSIWSRLQETGLRGKCECIRGR 700
701 KATLEELQTVHSEAHTLLYGTNPLNRQKLDSKKLLGSLTSMFVRLPCGGV 750
751 GVDSDTIWNEVHSSGAARLAVGCVIELVFKVATGELKNGFAVVRPPGHHA 800
801 EESTPMGFCYFNSVAIAAKLLQQRLNVSKILIVDWDVHHGNGTQQAFYND 850
851 PNVLYISLHRYDDGNFFPGSGAPDEVGTGAGVGFNVNMAFTGGLDPPMGD 900
901 TEYLTAFRTVVMPIANEFAPDVVLVSSGFDAVEGHPTPLGGYNLSAKCFG 950
951 YLTKQLMGLAGGRVVLALEGGHDLTAICDASEACVSALLGNELDPLPEKV 1000
1001 LQQRANANAVHSMEKVIEIHSKYWHSLQRYASTVGYSLVEAQKCENEEAE 1050
1051 TVTAMASLSVGVKPAEKRPDDEPMEEEPPL 1080
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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