 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VX91 from www.uniprot.org...
The NucPred score for your sequence is 0.72 (see score help below)
1 MDRYDMEDVVVAPPAECSSPLKEWRLKRQAGTLDRSDIIEFLKRESPKYF 50
51 DYQTSATVKDTNVITLKCMFKESLAKEEIIDVVVEFMLGDNPSSALEKLR 100
101 LEGNTATVCGKVFKNGEPTYSCRECGVDPTCVLCVNCFKRSAHRFHKYKM 150
151 STSGGGGCCDCGDDEAWKKDQYCELHLANRKNPLESKILTDAVLERVEIC 200
201 FGAILAFCVSYLEIEPNASLQCLDGNVEGGQVDGAQYCTVLYNDESHTFD 250
251 QVIQTLTKIAKCRAKDAMEIVAAIDREGRAVVKCDTFEECNKLKVSIENQ 300
301 MILPTSLVSTARNNQSLRTSVLHIGAVACQQFALQLLGWFQEFLVRHYLF 350
351 RKTFSELVQRKQETFCIRHILEYDVKLWKTARTCWHRLLISGMLMEYDNK 400
401 MILAQEFSRRYATIVEDFISDDHDHAFSIVSLSVQLFTVPSIAHHLIAHE 450
451 GIFDKLLHTFYHVAIEKFIRNKTLHFSKNIASLTFFKRANYILYDLRYLL 500
501 SLKPDVLSNDLRNGFLEGCRALMRVLNVMQGMESMTRQTGQHMDYEPEWE 550
551 CAFNLHIKLATTISQVIDWASGDVKLLRKLYKMTMRALVSNSFIVGGEKV 600
601 MQPKKVADHVANCLVYDISVQPVSIHLPLSRFFAGIYLHLGAHDLTYDGL 650
651 QTETEALSIKLTPREIIEPVLCTQAMIAQVGAGLWRRNGYTLLHQLYFYR 700
701 NVRCRVEMLDRDIACLQIGASLMESNEFLIHVLNRFNTIPWLQENYWSLL 750
751 SGNEMNDDIIREASIFDEFLELLIVIIGERWMPGVSMVTEEDRLRKEIIQ 800
801 LLCIKPYSHSELSRALPDGNSGNSDNVFEEVINTVAVFKKPVGADSKGVY 850
851 ELKEHLLKEFNMYFYHYTKEDKSKAEELQRERRKAKKQLVCCPPPMLPKL 900
901 TPAFTPMANILQCPVFLNICSLIMERALNAYSRSFTESHLQKVLHLLGYA 950
951 IQEELSEHYPFLSFYERSQEYGILEKLEELARCPRLEAHYDFVLWTIERF 1000
1001 KQLQAKQAPSDGRAGPSCSQQGTGGKLSLSAEEQAREERENRARLAAERR 1050
1051 AHIMAQMQKAQKSFISSNAEMFADTENETRKESASTGPMDWEDIPPEEEQ 1100
1101 GAVALESKVACLGPDRKFYHGTDDTFKCILCFENCAISRGGRQLVSSAFV 1150
1151 QTSRVIFTTPNLRNSQSALHISCCGHVMHYSCWLEYFTNEEFKELRRPHR 1200
1201 NRAALAQAANVEFQCPYCRTLSNAIIPVTETLPAFSAPPSPNESYLPLDS 1250
1251 FVEIMSTLAIELGNVKDHELTTLPSVSNILRLSGVVGGLAQFERSVQLIK 1300
1301 NPPRLHADYIEGIEFLKKALLNTMKIQQSHLKDHPAIESIEMVPILWDSC 1350
1351 SYTLQALEIYLYAVEKPLKAELSMRHQSCARNLVRACSRSSALEWETDLP 1400
1401 LLPPMRSQAEFSSRLLDTIFNQNDTSVLEWDCFRVLVPFQFGVLNLMVPE 1450
1451 KGYKTIIPSGSMFDFYIMQTMFLAQLTKAVLCFDVEKEKAKRAEKAPNSE 1500
1501 LTQLDYIEQLPSRIRDNMIDFYRRYNIPARVLQKTKQKQLVEEESEENQG 1550
1551 HGQTVVIPCESHHLALLLEYVQRQMSSFLRCSCLFYRFLTDVDFPDTFPT 1600
1601 DQPDRFDLMCQYLGLDPMLGVYFDMETVYATMMHSFASHPHIDREVEQRC 1650
1651 QPDARRSLQVEPCLRPLPRLKVLCDDFSDLINSVSDIFCPNNEREEMKTP 1700
1701 TMCLICGLILCGQSYCCQPELGKVSVGACTHHAHACGAEVGIFLRIRDCQ 1750
1751 VVYLGRGKGCFVPPPYLDEYGETDMGLRRGNPLRLSQAAYRKIYLQWLGH 1800
1801 GLHGEIARLNDNANVAAAAQWHHM 1824
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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