 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8IZH2 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MGVPKFYRWISERYPCLSEVVKEHQIPEFDNLYLDMNGIIHQCSHPNDDD 50
51 VHFRISDDKIFTDIFHYLEVLFRIIKPRKVFFMAVDGVAPRAKMNQQRGR 100
101 RFRSAKEAEDKIKKAIEKGETLPTEARFDSNCITPGTEFMARLHEHLKYF 150
151 VNMKISTDKSWQGVTIYFSGHETPGEGEHKIMEFIRSEKAKPDHDPNTRH 200
201 CLYGLDADLIMLGLTSHEAHFSLLREEVRFGGKKTQRVCAPEETTFHLLH 250
251 LSLMREYIDYEFSVLKEKITFKYDIERIIDDWILMGFLVGNDFIPHLPHL 300
301 HINHDALPLLYGTYVTILPELGGYINESGHLNLPRFEKYLVKLSDFDREH 350
351 FSEVFVDLKWFESKVGNKYLNEAAGVAAEEARNYKEKKKLKGQENSLCWT 400
401 ALDKNEGEMITSKDNLEDETEDDDLFETEFRQYKRTYYMTKMGVDVVSDD 450
451 FLADQAACYVQAIQWILHYYYHGVQSWSWYYPYHYAPFLSDIHNISTLKI 500
501 HFELGKPFKPFEQLLAVLPAASKNLLPACYQHLMTNEDSPIIEYYPPDFK 550
551 TDLNGKQQEWEAVVLIPFIDEKRLLEAMETCNHSLKKEERKRNQHSECLM 600
601 CWYDRDTEFIYPSPWPEKFPAIERCCTRYKIISLDAWRVDINKNKITRID 650
651 QKALYFCGFPTLKHIRHKFFLKKSGVQVFQQSSRGENMMLEILVDAESDE 700
701 LTVENVASSVLGKSVFVNWPHLEEARVVAVSDGETKFYLEEPPGTQKLYS 750
751 GRTAPPSKVVHLGDKEQSNWAKEVQGISEHYLRRKGIIINETSAVVYAQL 800
801 LTGRKYQINQNGEVRLEKQWSKQVVPFVYQTIVKDIRAFDSRFSNIKTLD 850
851 DLFPLRSMVFMLGTPYYGCTGEVQDSGDVITEGRIRVIFSIPCEPNLDAL 900
901 IQNQHKYSIKYNPGYVLASRLGVSGYLVSRFTGSIFIGRGSRRNPHGDHK 950
951 ANVGLNLKFNKKNEEVPGYTKKVGSEWMYSSAAEQLLAEYLERAPELFSY 1000
1001 IAKNSQEDVFYEDDIWPGENENGAEKVQEIITWLKGHPVSTLSRSSCDLQ 1050
1051 ILDAAIVEKIEEEVEKCKQRKNNKKVRVTVKPHLLYRPLEQQHGVIPDRD 1100
1101 AEFCLFDRVVNVRENFSVPVGLRGTIIGIKGANREADVLFEVLFDEEFPG 1150
1151 GLTIRCSPGRGYRLPTSALVNLSHGSRSETGNQKLTAIVKPQPAVHQHSS 1200
1201 SSSVSSGHLGALNHSPQSLFVPTQVPTKDDDEFCNIWQSLQGSGKMQYFQ 1250
1251 PTIQEKGAVLPQEISQVNQHHKSGFNDNSVKYQQRKHDPHRKFKEECKSP 1300
1301 KAECWSQKMSNKQPNSGIENFLASLNISKENEVQSSHHGEPPSEEHLSPQ 1350
1351 SFAMGTRMLKEILKIDGSNTVDHKNEIKQIANEIPVSSNRRDEYGLPSQP 1400
1401 KQNKKLASYMNKPHSANEYHNVQSMDNMCWPAPSQIPPVSTPVTELSRIC 1450
1451 SLVGMPQPDFSFLRMPQTMTVCQVKLSNGLLVHGPQCHSENEAKEKAALF 1500
1501 ALQQLGSLGMNFPLPSQVFANYPSAVPPGTIPPAFPPPTGWDHYGSNYAL 1550
1551 GAANIMPSSSHLFGSMPWGPSVPVPGKPFHHTLYSGTMPMAGGIPGGVHN 1600
1601 QFIPLQVTKKRVANKKNFENKEAQSSQATPVQTSQPDSSNIVKVSPRESS 1650
1651 SASLKSSPIAQPASSFQVETASQGHSISHHKSTPISSSRRKSRKLAVNFG 1700
1701 VSKPSE 1706
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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