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

NucPred

Fetching Q9D219 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MHPSNPKVRSSPSGNTQSSPKSKQEVMVRPPTVMSPSGNPQLDSKFSNQG    50
  51  KPGGSASQSQPSPCDSKSGGHTPKALPGPGGSMGLKNGAGNGAKGKGKRE   100
 101  RSISADSFDQRDPGTPNDDSDIKECNSADHIKSQESQHTPHSMTPSTATA   150
 151  PRSSTPSHGQTPAPEPISAQKTPAKVVYVFSTEMANKAAEAVLKGQVETI   200
 201  VSFHIQNISNSKSERSTAPLNTQIPTLRNDPKPLPQQPPAPANQDQNSSQ   250
 251  NARLQPTPPIQAPAPKPTAAPRPLDRESPGVENKLIPPVGSPGSSTPLPP   300
 301  DGTGPNSTPNNRAVTPVSQGSNSSSADPKAPPPPPVSGGEPPTLGENPDG   350
 351  LSQEQLEHRERSLQTLRDIQRMLFPDEKEFTAGQTGGPQQNTGVLDGPQK   400
 401  KPDGPIQAMMSQSQSLGKGPGPRTDVGAPFGPQGHRDVPFSPDEMVPPNM   450
 451  SSQSGPIGPDHLDHMTPEQIAWLKLQQEFYEEKRRKQEQVVVQQCSLQDM   500
 501  MVHQHGPRGVVRGPPPPYQMAPGEGWAPGAEPFPDGINISHSLPPRGMAP   550
 551  HPNMPGSQMRLPGFAGMINSEMEGPNVPNPASRPGLSGVSWPDDVPKIPD   600
 601  GRNFPPGQGVFSGPGRGERFPNPQGLSEEMFQQQLAEKQLALPPGMSMEG   650
 651  IRPGMEMNRMIPGSQRHMEPGSNPIFPRIPVEGPLSPSRGDFPKGMPPQI   700
 701  GPGRELEFGMVPGGMKGEVNLNVNMGSSSQMIPQKMREAGAGPEEMMKLR   750
 751  PGSSEMLPAQQKMVPLPFGEHPQQEYGVGPRPFLPMSQGPGSNSGLRNLR   800
 801  EPIGPDQRTNSRLSHMPPLPLNPSSNPTSLSTAPPVQRGLGRKPLDISVA   850
 851  GSQVHSPGINPLKSPTMHQVQSPMLGSPSGNLKSPQTPSQLAGMLAGPAA   900
 901  AASIKSPPVLGSAAASPVHLKSPSLPAPSPGWTSSPKPPLQSPGIPPNHK   950
 951  APLTMASPAMLGSVESGGPPPPTASQPASVNIPGSLPSSTPYPMPPEPTL  1000
1001  SQNPLSIMMSRMSKFAMPSSTPLYHDAIKTVASSDDDSPPARSPNLPSMN  1050
1051  SMPGMGINTQNPRISGPNPVVPMPTLSPMGMTQPLSHSNQMPSPNAMGPS  1100
1101  IPPHGVPMGPGLMSHNPIMGHGSQEPPMVPQGRMGFPQGFPPVQSPPQQV  1150
1151  PFPHNGPTGGQGNFPGGIGFPGEGPLGRPSNLPQSSADPALCKPGGPGAP  1200
1201  DSFTVLGNSMPSVFTDPDLQEVIRPGATGIPEFDLSRIIPSEKPSQTLQY  1250
1251  FPRGEVPGRKQPQGPGPGFSHMQGMMSDQAPRMGLALPGMGGPGPVGTPD  1300
1301  IPLGTSPSMPGHNPMRPPAFLQQGMMGPHHRMMSPAQSTVPGPATLMTNP  1350
1351  AAAVGMIPGKDRGPAGLYTHPGPVGSPGMMMSMQGMMGPQQNIMIPPQMR  1400
1401  PRGMAADVGMGGFSQGPGNPGNMMF                           1425

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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