 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q4PI89 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MADEERVPAPYFQDDEEGGASDEGEGVDLIKSHGNLVGSGGEDSSDEEED 50
51 DDPEEARRVAEGFIAEDDEEEEEDSEARRDRRRRRKKKRKQNEQDFEVDE 100
101 DDLELLAENTGQPRRKEAGRLKRFRRGSASPPADDEAAARQRTLDQIFED 150
151 DDEDEDDIRSGRRGVNYDDDDEDLPSVGQALRAGVARKQREVVGAYEDDG 200
201 LDDFIEEDEDDEEMQGLDEEEREARRQQRREEKRKARLSGSAADPAKAGI 250
251 DHEAWDEIHEIFGNGEDYFWALEDEEEDAFDEEKKNKMEYKDIFEPAQIA 300
301 ERMLTEDDERIKRIDIPERLQLACPGEEGLKLLERKLTDTELFEAAKWAS 350
351 TRISQRTAAEFLDEAGLFHRQRSEFINAVQLMLSYMLNDLLEVPFLFQHR 400
401 FDELEHLTFDEVERQYRSIDLLTRRELYTLSGLGLKFKTLLVRKDQLRAT 450
451 FNKIHVDVKTEPIQDDELDGGLDAMPADESRAARVESSQRQRAIFEDMLA 500
501 QAASLEEISDITEYLTLRYGQQMRDAQALTSNGTDQAASDLQGLTLTSDP 550
551 LVSATPAFKKPSLVGQYERNKKTVLAELAKKFGITSDELASNVTSHTRQY 600
601 SPRDPEESPFKFAEQFTGSAWGAHSPEIALAKAKMMLSQEIGKDPILKRE 650
651 MRQLFKDAAEINIEPTERGMTVIDDQHPYANFKFIANKPARLVPQNPSQY 700
701 LQMLQAEDELLIKLDIDLKDVVLTRFEARLYNNYASEGVGELSNAWNEQR 750
751 RDVIREALKTHLVPNGRIWLKEFLREESRETLLRHVDVLMTKRVQEGPFM 800
801 SKSMMARNRDPKIEEEDRIPRVLAVSHGGGDPRKDVVQAVYLDERGRFRE 850
851 HATFDDLRPLSARQMQERELELERTRGKAEFVDHRADFVKLLKQRRPDIV 900
901 VVSGWSVRTAELKRHVQELADTAHQEICDADRLHSDLERDQAVIDVVTCH 950
951 DDVARIYQHSSRAAEEFPELSELGRYCLALARYAQSPVNEFAALGSDLTA 1000
1001 VILDPNQRLLPQDRLRLHFERCIGAVVNENGVEINQAMTSTYLQTMLPFV 1050
1051 AGLGPRKAHALVNAISTKLEGTLINRTLLISRNILTFQVFQNCASFLRIE 1100
1101 QDMLLEADEDDVPDVLDSTRIHPEDYDFPRKMAADALNKHEEDLEGEHPS 1150
1151 LPCKELMEDADPADKLNTLDLDNYATMLFERKGERKRATLHSCRTELIKP 1200
1201 YDDLREKQSEPSLEEMLTMFTGETSKTLAEGFVVSVEVTRVQEGNRMQEG 1250
1251 HIKCRLDSGIEGTIEAEHAVEHYTPGSVRLRDLVRPQQTLDALVRKIDYK 1300
1301 MCTVQLSISPWELQHRATHQGKTPIDIKFYDRRKADQWNEHAAAKAKLRI 1350
1351 QARRQNRVIDHPNYHNFNYKAAVTFLRSQPRGTVVVRPSSKGDDHLAVTW 1400
1401 KVDDDVYQNIDVTELDKESEYSLGRVLRIEGMGSYSDLDELIVNHVKPMV 1450
1451 HMVEMMMNHEKYKGADEEDLHRFLTNWSLANPSRSVYAFGLNKDRPGYFN 1500
1501 LSFKANRDAAIQTWPVKVLPNAFKLGPADQLADVAALCNAFKTQYTTQAS 1550
1551 MARGAKTPYGGGRTPAPGMGGATPLGGRTPYGGVRNGMAGSATPGQGVAG 1600
1601 GYTTPMINVASATPNPYGGAYGRNGAAGGYGAPAAGGPPGRPPSMPGAPP 1650
1651 MMPPGMASGGGAPSYAPPFAGAGEPGPPPARPPVPHGMHPDRFAQAEYGG 1700
1701 ASQQSYGENSGGAGGYGGGYRGY 1723
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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