 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2LAE1 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MDCKENGVGDASGCNIDANSLASNLAMNTNEDFYEKLSSRGQNLDSVSSL 50
51 EIPQTASSVNHTIEGQRKCFTEIEQMGYGNSNSQEDAGNTDDDLYVCYNA 100
101 DDTQEQGVVSGELEQSQELICDTDLLVNCNKLDDGKESQDTNVSLVSIFS 150
151 GSMQEKEAPQAKEDEGYGGTTLPIGGSGIDTESTFVNDAPEQFESLETTK 200
201 HIKPDEVESDGISYRFDDGGKEGRNGPSSDLDTGSSDDISLSQSFSFPDS 250
251 LLDSSVFGCSATESYLEDAIDIEGNGTIVVSPSLAITEMLNNDDGGLCSH 300
301 DLNKITVTETINPDLKLVREDRLDTDLSVMNEKMLKNHVGDSSSESAVAA 350
351 LSMNNGMAADLRAENFSQSSPIDEKTLDMEANSPITDSSLIWNFPLNFGS 400
401 GGIEVCNPENAVEPLRIVDDNGRIGGEVASASGSDFCEAGMSSSRRKARD 450
451 GKQCKVVQTKTSARHLRKSSRKKQSERDIESIFKCSKQKRSSLLKTSRSS 500
501 EWGLPSKTTEIFLQSNNIPYDGPPHHEPQRSQGNLNNGEHNRSSHNGNVE 550
551 GSNRNIQASSGSCLRLKVKFGKSGGQNPLNITVSKVSGNSLPGNGIVKAG 600
601 TCLELPGSAHFGEDKMQTVETKEDLVEKSNPVEKVSYLQSSDSMRDKKYN 650
651 QDAGGLCRKVGGDVLDDDPHLSSIRMVEECERATGTQSLDAETSPDSEVI 700
701 NSVPDSIVNIEHKEGLHHGFFSTPEDVVKKNRVLEKEDELRASKSPSENG 750
751 SHLIPNAKKAKHPKSKSNGTKKGKSKFSESAKDGRKNESHEGVEQRKSLN 800
801 TSMGRDDSDYPEVGRIESHKTTGALLDADIGKTSATYGTISSDVTHGEMV 850
851 VDVTIEDSYSTESAWVRCDDCFKWRRIPASVVGSIDESSRWICMNNSDKR 900
901 FADCSKSQEMSNEEINEELGIGQDEADAYDCDAAKRGKEKEQKSKRLTGK 950
951 QKACFKAIKTNQFLHRNRKSQTIDEIMVCHCKPSPDGRLGCGEECLNRML 1000
1001 NIECLQGTCPAGDLCSNQQFQKRKYVKFERFQSGKKGYGLRLLEDVREGQ 1050
1051 FLIEYVGEVLDMQSYETRQKEYAFKGQKHFYFMTLNGNEVIDAGAKGNLG 1100
1101 RFINHSCEPNCRTEKWMVNGEICVGIFSMQDLKKGQELTFDYNYVRVFGA 1150
1151 AAKKCYCGSSHCRGYIGGDPLNGDVIIQSDSDEEYPELVILDDDESGEGI 1200
1201 LGATSRTFTDDADEQMPQSFEKVNGYKDLAPDNTQTQSSVSVKLPEREIP 1250
1251 PPLLQPTEVLKELSSGISITAVQQEVPAEKKTKSTSPTSSSLSRMSPGGT 1300
1301 NSDKTTKHGSGEDKKILPRPRPRMKTSRSSESSKRDKGGIYPGVNKAQVI 1350
1351 PVNKLQQQPIKSKGSEKVSPSIETFEGKLNELLDAVGGISKRRDSAKGYL 1400
1401 KLLLLTAASRGTDEEGIYSNRDLSMILDALLKTKSKSVLVDIINKNGPFA 1450
1451 GMESFKDSVLSFTEHDDYTVHNIARSFRDRWIPKHFRKPWRINREERSES 1500
1501 MRSPINRRFRASQEPRYDHQSPRPAEPAASVTSSKAATPETASVSEGYSE 1550
1551 PNSGLPETNGRKRKSRWDQPSKTKEQRIMTILSQQTDETNGNQDVQDDLP 1600
1601 PGFSSPCTDVPDAITAQPQQKFLSRLPVSYGIPLSIVHQFGSPGKEDPTT 1650
1651 WSVAPGMPFYPFPPLPPVSHGEFFAKRNVRACSSSMGNLTYSNEILPATP 1700
1701 VTDSTAPTRKRELFSSDIGTTYFRQQKQSVPPWLRNNGGEKTANSPIPGN 1750
1751 LTLEKKLNS 1759
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.) |
Go back to the NucPred Home Page.