 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UTK5 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSSGGLEDDIQLVHEFLDVSFEDIKPLVSVNGFAVFISAIKTKVKDINAL 50
51 KDQLVLQEVNHEHKENVLTKKINFLEQQLQSSNNQAEESRNLISVLRNEN 100
101 ESLKTNLENQNKRFDALTTENQSLRRANSELQEQSKIASEQLSIAKDQIE 150
151 ALQNENSHLGEQVQSAHQALSDIEERKKQHMFASSSSRVKEEILVQEKSA 200
201 LVSDLASLQSDHSKVCEKLEVSSRQVQDLEKKLAGLAQQNTELNEKIQLF 250
251 EQKRSNYSSDGNISKILETDPTSIKELEEEVETQKRLTALWESKSSELQS 300
301 EVAALQEKLTSQQSLYNNVTEELNNNKQQLLISENSLRELQEKYDSVVSE 350
351 LQVVKENKNTSVSAGVGLFSPLAQKLSAVQNPEFSFTKVYSDNMKLQQKV 400
401 SSLKLQLDRLTNKFSSFCEQVKQRIPVVKQQRSEIVRNNIYMNFLSESLE 450
451 TSNNNLTKVQAELLSTKMRQEACYLQLTASRTQCSDLSREVICLMAELDH 500
501 LNETKSRNVPATVQVALDEYAQNPSTASETLVNKELANFSSIKEAVSKTL 550
551 ELREKVRALECDVEIQKQTVQYQISNAVKENSNTLSEQIKNLESELNSSK 600
601 IKNESLLNERNLLKEMLATSRSSILSHNSSAGNIDDKMKSIDESTRELEK 650
651 NYEVYRNEMTAIQESLSKRNQDLLSEMEAIRKELENSKYQQQLSTDRLTN 700
701 ANNDVEAFKKEAKELRSINQNLQDIISRQDQRASKFAEELLHVNSLAERL 750
751 KGELNASKGEKDLRKRTQERLISENDKLLAERERLMSLVSDLQTFLNQQQ 800
801 LSDAARKVKFESEKESLSLSLQKLKESNEKMSNDLHSLQKSLEKSGIEYS 850
851 SRIKTLMLEKQSLSEDNRKLLDNQQMMEIKLQELNGVIELEKQRFSTLEA 900
901 KFTQQKNTSYSEREALLESSLSDLQSKHTSLESQYNYSLRNIEQLQAASK 950
951 LAEEMVERVKTEYDEYRLQTSESLEKNHLKITSLEQRIVILQDEIASSSL 1000
1001 RCENITKDSETRVALLLEENKHLNNELSSHRNAEKQHLEKENDYKQQLLL 1050
1051 VTEDLRKTREDYEKELLRHADARSTLQKLREDYTKALEQVEDLNKEIALK 1100
1101 AGINESQPFPISEKEDPLRQEVYVLKKQNAMLLTQLQSSNLNFAEITSPS 1150
1151 PDLDSVMKLGLSDLQNHVKRISKEMEIISCQRQLLFLENKKLKRTVESSN 1200
1201 RVIADLQRGITEKDVSSTSESVGERSNYLNMVALLNESNKSLRENLERNE 1250
1251 EVITELREKIETLKTDLANFRLNKEQLESQLQTEKAAVKKLENSNEEYKR 1300
1301 HNQEILLSLNSSTSTSSDASRLKNELVSKENLIEELNQEIGHLKSELETV 1350
1351 KSKSEDLENERAQNQSKIEQLELKNTKLAAAWRTKYEQVVNKSLEKHNQI 1400
1401 RQQLSQKTSELEAKVAECHQLNEQLNKPSATPTATTQSEPSTVSLEEFNS 1450
1451 TKEELSSTQRKLSEIMDILNTTKEELEKVRQNSNKSEGTSKDTEIPNEEE 1500
1501 MERKKVMQQEVLRLRSRIAKELQKNELLRKQNQVLQDQVKALQETVVSSE 1550
1551 EAESASVHADTKDLENLKKTEEMLSVTFQVIFNESISDFSTSTADFTTFV 1600
1601 QKEWEKRREILQKDVEEQVAQSHQKQLDNIRKELEMRNKLKLSMLEKNLA 1650
1651 RVRAELEQSKKKDSPAILSLEASKNTDSNKSNSEVPAAQVKEKKLIAKTH 1700
1701 SVDTNSPPKRSSSDAGMDVSNDVKKAK 1727
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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