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

NucPred

Fetching Q9U7E0 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MRVGVSESEDSDGHVIEDEDLEMARQIENERKEKRAQKLKEKREREGKPP    50
  51  PKKRPAKKRKASSSEEDDDDEEESPRKSSKKSRKRAKSESESDESDEEED   100
 101  RKKSKSKKKVDQKKKEKSKKKRTTSSSEDEDSDEEREQKSKKKSKKTKKQ   150
 151  TSSESSEESEEERKVKKSKKNKEKSVKKRAETSEESDEDEKPSKKSKKGL   200
 201  KKKAKSESESESEDEKEVKKSKKKSKKVVKKESESEDEAPEKKKTEKRKR   250
 251  SKTSSEESSESEKSDEEEEEKESSPKPKKKKPLAVKKLSSDEESEESDVE   300
 301  VLPQKKKRGAVTLISDSEDEKDQKSESEASDVEEKVSKKKAKKQESSESG   350
 351  SDSSEGSITVNRKSKKKEKPEKKKKGIIMDSSKLQKETIDAERAEKERRK   400
 401  RLEKKQKEFNGIVLEEGEDLTEMLTGTSSQRKLKSVVLDPDSSTVDEESK   450
 451  KPVEVHNSLVRILKPHQAHGIQFMYDCACESLDRLDTEGSGGILAHCMGL   500
 501  GKTLQVITFLHTVLMHEKIGEKCKRVLVVVPKNVIINWFKEFQKWLVDND   550
 551  EELDTIDVNELDSYKTIEDRRRALKAWHSSKTPSVMIIGYDLFRILTVED   600
 601  DPKKKKPKNRNRRLEKAKEDFRKYLQNPGPDMVVCDEAHKLKNDDSALSK   650
 651  CMVKILTKRRICLTGTPLQNNLMEYHCMVNFVKPGLLGTKTEFANRFVNI   700
 701  INRGRTKDASPLEVSFMKRRCHVLYDHLKKCVDRKDYRVLTEAIPPKQEY   750
 751  VINVRQTERQCALYNAFLNDIVGDSGLSKRLLPDYHMFSRIWTHPYQLVL   800
 801  HEQRMERERVMREDAEEEADFIDDGDGSESESEGSFKSGSESDSGKSVVL   850
 851  SSDDEGSSKKKKNGNKPEIKKTAPQKKRKFLNSDDEDEEDGEDTAMAILQ   900
 901  DGIRQSKRLAGEEADLRDTDTPPEYTGWFARLGLVKEEDRDDFALSNKLI   950
 951  LLVEIIKKCEEIGDKLLVFSQSLESLTLIKRMLEYMAGTGQWFADGHEAL  1000
1001  NAEGEETWSWLEGEDYMTIDGSVQSGKRDAVQTSFNDPLNLRARLMLIST  1050
1051  RAGSLGTNMVAANRVIIFDACWNPSHDTQSLFRVYRFGQTKPVYIYRFIA  1100
1101  QGTMEERIYKRQVTKESTSMRVVDEAQIQRHYLGNDLTELYQFTPSTFDP  1150
1151  DVEISCAPPKDRLLADVIHKNQHAVVDYIEHDTLFANVEDEKLTEQEMKD  1200
1201  AWTDYEKDKSGMPVRAQYAAPPMPGFPNGMIVGQNVQALLQNRMNQGIRV  1250
1251  DQMQHDILFKELQKMRIKDAGTAVKIVLLRNLLEQILPYIPDEMRGGMSE  1300
1301  FNTHFIRLVHETDRKMETPADLLRKSLESFKTVIKMVKMIPTCREPLARM  1350
1351  TRDYPYLFA                                           1359

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.