 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UPS8 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MKKIFSKKGESPLGSFARRQRSSAGGGGEPGEGAYSQPGYHVRDRDLGKI 50
51 HKAASAGNVAKVQQILLLRKNGLNDRDKMNRTALHLACANGHPEVVTLLV 100
101 DRKCQLNVCDNENRTALMKAVQCQEEKCATILLEHGADPNLADVHGNTAL 150
151 HYAVYNEDISVATKLLLYDANIEAKNKDDLTPLLLAVSGKKQQMVEFLIK 200
201 KKANVNAVDKLESSHQLISEYKEERIPKHSSQNSNSVDESSEDSLSRLSG 250
251 KPGVDDSWPTSDDEDLNFDTKNVPKPSLAKLMTASQQSRKNLEATYGTVR 300
301 TGNRTLFEDRDSDSQDEVVVESLPTTSIKVQCFSHPTYQSPDLLPKPSHK 350
351 SLANPGLMKEEPTKPGIAKKENGIDIIESAPLEQTNNDNLTYVDEVHKNN 400
401 RSDMMSALGLGQEEDIESPWDSESISENFPQKYVDPLAGAADGKEKNIGN 450
451 EQAEDVFYIPSCMSGSRNFKMAKLEDTRNVGMPVAHMESPERYLHLKPTI 500
501 EMKDSVPNKAGGMKDVQTSKAAEHDLEVASEEEQEREGSENNQPQVEEER 550
551 KKHRNNEMEVSANIHDGATDDAEDDDDDDGLIQKRKSGETDHQQFPRKEN 600
601 KEYASSGPALQMKEVKSTEKEKRTSKESVNSPVFGKASLLTGGLLQVDDD 650
651 SSLSEIDEDEGRPTKKTSNEKNKVKNQIQSMDDVDDLTQSSETASEDCEL 700
701 PHSSYKNFMLLIEQLGMECKDSVSLLKIQDAALSCERLLELKKNHCELLT 750
751 VKIKKMEDKVNVLQRELSETKEIKSQLEHQKVEWERELCSLRFSLNQEEE 800
801 KRRNADTLYEKIREQLRRKEEQYRKEVEVKQQLELSLQTLEMELRTVKSN 850
851 LNQVVQERNDAQRQLSREQNARMLQDGILTNHLSKQKEIEMAQKKMNSEN 900
901 SHSHEEEKDLSHKNSMLQEEIAMLRLEIDTIKNQNQEKEKKCFEDLKIVK 950
951 EKNEDLQKTIKQNEETLTQTISQYNGRLSVLTAENAMLNSKLENEKQSKE 1000
1001 RLEAEVESYHSRLAAAIHDRDQSETSKRELELAFQRARDECSRLQDKMNF 1050
1051 DVSNLKDNNEILSQQLFKTESKLNSLEIEFHHTRDALREKTLGLERVQKD 1100
1101 LSQTQCQMKEMEQKYQNEQVKVNKYIGKQESVEERLSQLQSENMLLRQQL 1150
1151 DDAHNKADNKEKTVINIQDQFHAIVQKLQAESEKQSLLLEERNKELISEC 1200
1201 NHLKERQYQYENEKAEREVVVRQLQQELADTLKKQSMSEASLEVTSRYRI 1250
1251 NLEDETQDLKKKLGQIRNQLQEAQDRHTEAVRCAEKMQDHKQKLEKDNAK 1300
1301 LKVTVKKQMDKIEELQKNLLNANLSEDEKEQLKKLMELKQSLECNLDQEM 1350
1351 KKNVELEREITGFKNLLKMTRKKLNEYENGEFSFHGDLKTSQFEMDIQIN 1400
1401 KLKHKIDDLTAELETAGSKCLHLDTKNQILQEELLSMKTVQKKCEKLQKN 1450
1451 KKKLEQEVINLRSHIERNMVELGQVKQYKQEIEERARQEIAEKLKEVNLF 1500
1501 LQAQAASQENLEQFRENNFASMKSQMELRIKDLESELSKIKTSQEDFNKT 1550
1551 ELEKYKQLYLEELKVRKSLSSKLTKTNERLAEVNTKLLVEKQQSRSLFTT 1600
1601 LTTRPVMEPPCVGNLNNSLDLNRKLIPRENLVISTSNPRASNNSMENYLS 1650
1651 KMQQELEKNITRELKEAAAELESGSIASPLGSTDESNLNQDLVWKASREY 1700
1701 VQVLKKNYMI 1710
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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