| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5B993 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MTARGKNVKIQTLATENEIFLYDRRYVSEQDNADLPKLPSPQPLVLDKPP 50
51 DTLSDRNDLQAWRNLYAARKTWAAELTERCEMADTSIRELNERTGIVNRA 100
101 ASVALENLKTHVAALENRFQEAQAWAKELSREQKSALEEWKRALANLENI 150
151 PARKEFSFLGRPSTPKKDADRATGTLLDYVDAVEVQKAGPEASAASSRFA 200
201 QQIQDIERAVGEITAGTQRLLDDVPNSRTDTADGLLQEIEPLSRKIQSDY 250
251 EHVLGLSNNSKTLANISRLALNHTQDILPSMLEIAMEIRESLAAAVRQYD 300
301 AATKSALGRTKLISAIQSRLADVQAHIANLTFQSDAFDLLYSVFHMPLVY 350
351 GSVLIESVRRHEFNEKMKSDSLTLAEELSIFQDEEQRRRKKWVKNMEDFL 400
401 SVTDTTTPGIEVNLRGHEFDWPIVTRKDIETYIEDLRSNPGTANAAQELA 450
451 QAFKELDAPTRVQRRRAKAFKQGSIFDLSRSSLLLHSDEIVRSLRDEKLK 500
501 LEEKLRGSESRIRKLEDLLHRHSHLGRPSSGNFSIDFPASPASPHPDPMS 550
551 RRSSVSSRRLSSNQTSEEKNLVNRIVHLEADLAIERETVQRLQREADAER 600
601 QSNTNKMQEAQSTKNDLIGNLEARQREFSDERRYLEGEVKRFKIRVEELE 650
651 EELDRLTDSRDHEKQDADERMHQLELELQDAHARADAEMRKANNLLEQMQ 700
701 SHREAADRSKLRMDELEKQATERTQKDQEVRHALQAAFMNLSPGGSVPDE 750
751 IVDIIKAIDVLSEGLTIHAKTAEDNAMKAAAENKTLIEQLEKMESNYENA 800
801 KSASEQYQTQLTQAREEVEQEQSKVKAIESELNDERASLLELESKLAAGE 850
851 TGAGALREHVAEEEQKLNNMSQQLAETEARARRSEEEALQWRKRAEALSE 900
901 SDKQVAARIDIRTARLEELSRQLFGQVEKLERMLEQLGFTVIRQDGEIVV 950
951 QRSSKVNALSATADTLSQSGVVSVKPDPSLLNWMQGEHPEEETERFNAFL 1000
1001 ESLHQFSVDIFGDAVVKRVKDIEVLARKWQKEARGYRDKYHRMQSEAHDK 1050
1051 IAYRSFKEGDLALFLPTRNQAIRSWAAFNVGAPHYFLREQDVHKLQARDW 1100
1101 LLARITKIEERVVDLSKSMNGGNPDRRSIGEASDGASIDDENPFELSDGL 1150
1151 RWYLLDATEEKPGAPATPGLGKSTVAPAHVDAKGSIRLKRTPAGGNVTKT 1200
1201 LTRSLDSRRNSSASASIKRGTPPSRANDSTTDLVRPAQAESESIAAATDS 1250
1251 KSQSQSQSQERERRQEAQGTAVIFDEVRRDQLQGP 1285
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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