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

NucPred

Fetching Q9JMH4 from www.uniprot.org...

The NucPred score for your sequence is 0.54 (see score help below)

   1  MDVTKKNKRDGTEVTERIVTEIVTTRLTSLPPKGSTSNGYAKTGSLGGGS    50
  51  RLEKQSLTHGSSGYINSSGSIRGNASTSSYRRAHSPASTLPNSPGSTFER   100
 101  KTHMTRHGTYEGSSSGNSSPEYPRKELASSATRGRSQTRESEIRVRLQSA   150
 151  SPSTRWTELDEVKRLLKGSRSASASPTRNTSSTLPIPKKGTVETKMVTAS   200
 201  SHSVSGTYDTTALDTNLPSHMWSSTLPAGSSMGTYHNNMTTQSSSLLNTN   250
 251  AYSAGSVFGMPNNMASCSPTLLPGLSSCSSVFGMQNNLAPSSSVPAHGTT   300
 301  TAPTAYGVKKNVPQPPTVTSTGVSTSATCTTSVQSDDLLHKDCKFLILEK   350
 351  DNVPSKKEMELLIMTKDSGKVFTASPASVSTTSFSEDTLKKEKQAAYAAD   400
 401  ACLKADINGDLNTVSTKGKATSVENHNYDRGGGSGGGARGGGGSGGGGGG   450
 451  GGTWGAAPAWCPCGSCCSWWKWLLGLLLTWLLLLGLLFGLIALAEEVRKL   500
 501  KARVDELERTRVQYFEDKTERSSKDRLLGDMPGVGPGLGKAELDGHSQEA   550
 551  IWLFVRNKLMTEQENGNLRGNPGPKGDMGSQGPKGDRGLPGTAGIPGPLG   600
 601  HPGPEGPKGQKGSIGDPGMEGPIGQRGLEGPMGPRGEPGPPGSGEKGDRG   650
 651  IAGEQGPRGLPGVPGSVGPRGPNGSPGPQGPPGSTGPQGLRGEVGLPGVK   700
 701  GDKGLAGPPGPKGDQGEKGPRGLTGEPGVRGLPGAVGEPGAKGAMGPAGP   750
 751  DGQQGPRGEQGLTGMPGTRGLPGPSGDPGKPGVTGPQGPQGLPGSPGRPG   800
 801  TKGEPGAPGRVMTAEGSSTITVPGPPGPPGAMGPPGPSGTPGPAGPAGLP   850
 851  GQTKAQRGEPGLAGDSFISSGSSISEVLAAQGVDLRGPLGPPGPRGPPGP   900
 901  SIPGPPGPRGPPGEGVPGPPGLPGSFLTDSETFFSGPPGPPGPPGPKGDQ   950
 951  GDPGVPGTPGIPGGHSHGESSSTTYRQGPPGPPGPPGPPGSFSSSGQDIQ  1000
1001  RYIAEYMQSDSIRTYLSGVQGPPGPPGPPGPVITITGETFDYSQLASQVV  1050
1051  SYLRTSGYGVSLSSASSEDILAMLRRNDVWQFLRQHLVGPPGPPGPPGVG  1100
1101  GDGSLLSLDYGELSRHILNYMSSSGISFGHPGPPGPPGLPGTSYEELLTM  1150
1151  LRGSDYRDIIGPPGPPGPPGPRGPPGVSAALATYAAENSDNFRSELIGYL  1200
1201  TSPDVRSFIIGPPGPPGPQGPPGDSHLRDNYSWGSSSSARRGTAYSSSVG  1250
1251  MGGANGGSLGEGRTFGTGDGGPYGTDIGPGGGYGAAAGGIYGTDGDSFRA  1300
1301  GFTGDLDYNKLAVRVSESMQRQGLLQGMAYTVQGPPGVPGPQGPPGISKV  1350
1351  FSAYSNVTQDLMDFFRTHGAIPGPPGQKGEAGTPGPKGDRGLAGQRGPPG  1400
1401  PPGPRGQKGDKGDKGDQVYTGRRRRSIAIKP                     1431

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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