 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P46018 from www.uniprot.org...
The NucPred score for your sequence is 0.72 (see score help below)
1 MRSRSNSGVRLDGYARLVQQTILCYQNPVTGLLSASHEQKDAWVRDNIYS 50
51 ILAVWGLGMAYRKNADRDEDKAKAYELEQNVVKLMRGLLQCMMRQVDKVE 100
101 KFKYTQSTKDSLHAKYNTATCSTVVGDDQWGHLQVDATSLFLLFLAQMTA 150
151 SGLRIIFTLDEVAFIQNLVFYIEAAYKVADYGMWERGDKTNQGIPELNAS 200
201 SVGMAKAALEAIDELDLFGAHGGRKSVIHVLPDEVEHCQSILFSMLPRAS 250
251 TSKEIDAGLLSIISFPAFAVEDANLVNVTKSEIISKLQGRYGCCRFLRDG 300
301 YKTPREDPNRLHYDPAELKLFENIECEWPVFWTYFIIDGIFNGDALQVQE 350
351 YQEALEGILIRGKDGIRLVPELYAIPPNKVDEEYKNPHTVDRVPLGKLPH 400
401 LWGQSLYILSSLLAEGFLATGEIDPLNRRFSTSVKPDVVVQVTVLAENSH 450
451 IKELLRKHGVDVQSIADIYPIRVQPGRILSHIYAKLGRNKNMKLSGRPYR 500
501 HIGVLGTSKLYVIRNQIFTFTPQFTDQHHFYLALDNEMIVEMLRIELAYL 550
551 CTCWRMTGRPTLTFPITHTMLTNDGSDIHSAVLSTIRKLEDGYFGGARVQ 600
601 LGNLSEFLTTSFYTYLTFLDPDCDEKLFDDASEGSFSPDSDSDLGGYLEE 650
651 TYNQVTESQDELDKYINHLLQSTYSKCHLPPLCKKMEDHNVFSAIHSTRD 700
701 ILSMMAKAKGLEVPFAPMTLPTKALSVHRKSLNLVDSPQPLLKRILKRLH 750
751 WPKDERGDVDCEKLVEQLKDCCTLQDQADILYILYVLKGPSWDTALSGQH 800
801 GVTVHNLLSELYGKAGLNQEWGLIRYISGLLRKKVEVLAEACADLLSHQK 850
851 QLTVGLPPEPREKTISAPLPPEELTELIYEASGEDISIAVLTQEIVVYLA 900
901 MYVRAQPALFVEMLRLRIGLIIQVMATELARSLNCSGEEASESLMNLSPF 950
951 DMKNLLHHILSGKEFGVERSMRPIHSSASSPAISIHEVGHTGVTKTERSG 1000
1001 INRLRSEMKQMTRRFSADEQFFPVSQTVSSSAYSKSVRSSTPSSPTGTSS 1050
1051 SDSGGHHISWGERQGQWLRRRRLDGAINRVPVGFYQRVWKILQKCHGLSI 1100
1101 DGYVLPSSTTREMTPQEIKFAVHVESVLNRVSQPEYRQLLVEAIMVLTLL 1150
1151 SDTEMESIGGIIHVDQIVQMANQLFLQEQISTGAMDTLEKDQATGICHFF 1200
1201 YDSAPSGAYGTMTYLTRAVASHLQELLPSSGCQTQ 1235
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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