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

NucPred

Fetching Q62315 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MSKERPKRNIIQKKYDDSDGIPWSEERVVRKVLYLSLKEFKNAQKRQHGE    50
  51  GLAGSLKAVNGLLGNAQAKALGPASEQSENEKDDASQVSSTSNDVSSSDF   100
 101  EEGPSRKRPRLQAQRKFAQSQPNSPSTTPVKIVEPLLPPPATQISDLSKR   150
 151  KPKTEDFLTFLCLRGSPALPNSMVYFGSSQDEEDVEEEDDETEDVKATTN   200
 201  NASSSCQSTPRKGKTHKHVHNGHVFNGSSRSAREKEPAHKHRSKEATPGK   250
 251  EKHSEPRADSRREQASGAQPTAASAAASSAKGLAANHQPPPSHRSAQDLR   300
 301  KQVSKVNGVTRMSSLGAGTNSAKKIREVRPSPSKTVKYTATVTKGTVTYT   350
 351  KAKRELVKETKPNHHKPSSAVNHTISGKTESSNAKTRKQVLSLGGASKST   400
 401  GPAASGLKASSRLNPKSCTKEVGGRQLREGLRNSKRRLEEAQQVDKPQSP   450
 451  PKKMKGVAGNAEAPGKKASAASGEKSLLNGHVKKEVPERSLERNRPKRAA   500
 501  AGKNMLGKQAHGKTEGTPCENRSTSQPESSHKPHDPQGKPEKGSGKSGWA   550
 551  AMDEIPVLRPSAKEFHDPLIYIESVRAQVEKYGMCRVIPPPDWRPECKLN   600
 601  DEMRFVTQIQHIHKLGRRWGPNVQRLACIKKHLRSQGITMDELPLIGGCE   650
 651  LDLACFFRLINEMGGMQQVTDLKKWNKLADMLRIPKTAQDRLAKLQEAYC   700
 701  QYLLSYDSLSPEEHRRLEKEVLMEKEILEKRKGPLEGHTESDHHKFHSLP   750
 751  RFEPKNGLVHGVTPRNGFRSKLKEVGRAPLKTGRRRLFAQEKEVVKEEEE   800
 801  DKGVLNDFHKCIYKGRSVSLTTFYRTARNIMNMCFSKEPAPAEIEQEYWR   850
 851  LVEEKDCHVAVHCGKVDTNTHGSGFPVGKSEPFSRHGWNLTVLPNNTGSI   900
 901  LRHLGAVPGVTIPWLNIGMVFSTSCWSRDQNHLPYIDYLHTGADCIWYCI   950
 951  PAEEENKLEDVVHTLLQGNGTPGLQMLESNVMISPEVLCKKGIKVHRTVQ  1000
1001  QSGQFVVCFPGSFVSKVCCGYNVSETVHFATTQWTSMGFETAKEMKRRHI  1050
1051  AKPFSMEKLLYQIAQAEAKKENGPTLSTISALLDELRDTELRQRRLLFEA  1100
1101  GLHSSARYGSHDGNSTVADGKKKPRKWLQLETSERRCQICQHLCYLSMVV  1150
1151  QENENVVFCLECALRHVEKQKSCRGLKLMYRYDEEQIISLVNQICGKVSG  1200
1201  KHGGIENCLNKPTPKRGPRKRATVDVPPSRLPSS                  1234

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.)

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