 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q65Z40 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MTSRFGKTYSRKGGNGSSKFDEVFSNKRTTLSTKWGETTFMAKLGQKRPN 50
51 FKPDIQEIPKKPKVEEEDTGDPFGFDSDDESLPVSSKNLAQGKGSSYSES 100
101 SEAAQLEEVTSVFEANSKCSHVVGEDSFASDRCLLVEDTLIGKEKSISRI 150
151 PEDNANKSSCTKLLTSDKVENFSEEHEKNSHHFHKNAEDSTKKPNAETAV 200
201 ASEYKADETKETNDTWNSQSGKRTESPSESCPVKGSVRTGLYEWDNDFED 250
251 IRSEDCILSLDNESLLEMKDEDLKNRIGGLENLNETFEEDIIQSVLRPSN 300
301 CRTYCRANKARSSQGASNFDKLMDGTSQSLAKANSESSKDGLNQAKKGSA 350
351 SCGTSFRGTVGRTRDYTVLHPSCLSVCNVTIQDTMERSMDEFTASTPADL 400
401 GEAGRLRKKADIATSKTTTRFRPSNTKSKKDVKLEFFGFEDHDETGGDEG 450
451 GSGSSNYKIKYFGFDDLSESEDDDDDDCQVERKKDKKRTKTAPSPSQQPP 500
501 PESSDNSQDSQSSTNNAENLDFTEDLPGVPESVKKPISKQGDKSKENTRK 550
551 IFSGPKRSPTKAVYNARHWNHPDSEELPGPPIAKPQRVTVRLSSKEPNQK 600
601 DDGVFKAPAPPLKVIKTVTIPTQPYQEIVTALKCRKEDKELYTVVQHVKH 650
651 FNDVVEFGENQEFTDDIEYLLSGLKSTQPLNTRCLSVISLATKCAMPSFR 700
701 MHLRAHGMVAMVFKTLDDSQHHQNLSLCTAALMYILSRDRLNMDLDRASL 750
751 DLMIRLLELEQDASSAKLLNEKDMNKIKEKIRRLCETVHNKHLDLENITT 800
801 GHLAMETLLSLTSKRAGDWFKEELRLLGGLDHIVDKVKECVDHLSRDDED 850
851 EEKLVASLWGAERCLRVLESVTVHNPENQSYLIAYKDSQLIISSAKALQH 900
901 CEDLIQQYNRAENSICVADSNPLPYQNVTNHVGKAVEDCMRAIIGVLLNL 950
951 TNDNEWGSTKTGEQEGLIGTAMNCVLQVPKYLPQEQRFDIRVLGLGLLIN 1000
1001 LVEYSARNRHCLVNMQTSCSFDSSFSSGEGDHSLRLAGQVHAVQALVQLF 1050
1051 LERERAAQLAESKTDELIKDAPTTQHDKSGEWQETSGEIQWVSTEKTDGA 1100
1101 EEKQKKEEEDEELDLNKALQHAGKHMEDCIVASYTALLLGCLCQESPINV 1150
1151 TTVREYLPEGDFSIMTEMLKKFLSFMNLTCAVGTTGQKSISRVIEYLEHC 1200
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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