SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q2QLG9 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MATDGASCEPDSSRAPEDPAGATAEAPKKEFDVDTLSKTELRMLLSVMEG    50
  51  ELEARDLVIEALRARRKEVFIQERYGRFNLNDPFLALQRDYEAGAGDKEK   100
 101  KPVCTNPLSILEAVMAHCRKMQERMATQLAAAESRQKKLEMEKLQLQALE   150
 151  QEHKKLAARLEEERGKNKQVVLLLVKECKQLSGRVIEEAQRLEEVMAKLE   200
 201  EEKKRTSELEEELSAEKRRSTEMEAQMEKQLSEFDTEREQLRAKLSREEA   250
 251  HTTDLKEEVDKMKKMIEQLKRGGDGKPSLSLPRKTKDRRLVSASVGTEGP   300
 301  LTRSVACQTDLAVESAEPVKKSPLTVHVKPSPGSPHVSVKGSGGKPGMDR   350
 351  QASHGELMGSALPTLPPPSASRIEENGPSPGSTPDAPGSAAPPGSAAPPG   400
 401  SAAPPGSAAPPGSAAPHSFHSPCASAPPHPGLNPRIQAARFRFQGNANDP   450
 451  DQNGNTTPSPPSRDVSPTSRDNLVAKQLARNTVTQALSRFTSPPAGAAPR   500
 501  PGASPTGDGGAYPPVGRTGLKTPGVARVDRGNPPPIPPKKPGLSQTPSPP   550
 551  HPQLKVIMDSSRASNAGAKVDNKTVASPPSSLPQGSRVINEENLPKSSSP   600
 601  QLPPKPSIDLTVAPAGCAVSALATSQVGAWPAETPGLNHPACSDSSLVIP   650
 651  TTTASRSAINPVSASSCSPGASDSLLVTASGWSPSLTPLLMSGGPAPLAG   700
 701  RPTLLQQAAAQGNVTLLSMLLNEEGLDINYSCEDGHSALYSAAKNGHTDC   750
 751  VRLLLNAEAQVNAADKNGFTPLCAAAAQGHFECVELLIAYDAHINHAADE   800
 801  GQTPLYLACKNGNKECIKLLLEAGTNRNVKTRDGWTPVHAVVDTGDVDSL   850
 851  KLLMYHRAPARGNSLNEEEPKSDIFDLDEGEESPEGISKPVIPADLINYA   900
 901  NREGWTAAHIAASKGFKNCLEILCRHRGLEPEKRDKCNRTVHDVATDDCK   950
 951  HLLENLNALKIPVRISVGEIQPGNYGSNDFECENTICALHIRKQTSWDDF  1000
1001  SKAVSQALTNHFQAISSDGWWSLEDTALNDTADSNIGLSTSSVRAIMLGH  1050
1051  VPWSSGQSFTQSPWDFMKRNKVEQVTVLLSGPQEGCLSSVTYASMIPLHM  1100
1101  LQNYLRLIEQYRNVIFHGPEGSLQDYIVHQLALCLKHRQMAAGFSCEIVT  1150
1151  AEVDAGFSKEQLVDLFISSACLIPVKQSPVKKKIIIIILENLEKSSLSEL  1200
1201  LGDFLAPLENRSTESPCTVQKGNGMSACYYFHENCFLMGTIAKACLQGSE  1250
1251  LLVQQHFRWVQLRWDGEPMQGLLQRFLRRKVVNKFRGQVPSPCDLVCKTV  1300
1301  AWALSVWRQLNSCLARLGTPEALLGPKYFLSCPVIPGHAQATVKWMSKLW  1350
1351  NAVIAPRVQEAILSRASMKRQPGFGQTTAKKHPSQGQQAVVKAALSILLN  1400
1401  KAVLHGCPLPRAELDQHTADFKGGSFPLSLVSSYNSCSKKKESGAWRKVN  1450
1451  TSPRRKSGRFSSPTWNKADPSSEGLKNKTISQLNCNKNASLSKQKSLEND  1500
1501  LSLMLNLDQRLSLGSDDEVDLVKELQSMCSSKSESDISKIADSRDDLRTF  1550
1551  DSSGNNPAFSATVNNPRMPVSQKEVSPLSSHQTTECSNNSKSKPESGVSR  1600
1601  AKSFLPVPRSKATQCSQNTKRSSSSSNTRQIEINNNSKEENWNLHKNEQI  1650
1651  EKPNK                                               1655

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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.