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

NucPred

Fetching O35206 from www.uniprot.org...

The NucPred score for your sequence is 0.15 (see score help below)

   1  MTHRRTAQGRRPRWLLSIISALLSAVLQTRAATGSASQVHLDLTVLIGVP    50
  51  LPSSVSFTTGYGGFPAYSFGPGANVGRPARTLIPPTFFRDFAIGVAVKPN   100
 101  SAQGGVLFAITDAFQKVIYLGLRLSSVEDGRQRVILYYTEPGSHVSREAA   150
 151  VFSVPVMTNRWNRFAVTVQGEEVALFMDCEEQSQVRFQRSSWPLTFEPSA   200
 201  GIFVGNAGAMGLERFTGSIQQLTIYSDPRTPEELCEAQESSASGEASGFQ   250
 251  EMDEVAEIMEAVTYTQAPPKESHVDPISVPPTSSSPAEDSELSGEPVPEG   300
 301  TPETNLSIIGHSSPEQGSGEILNDTLEVHAMDGDPGTDDGSGDGALLNVT   350
 351  DGQGLSATATGEASVPVTTVLEAENGSMPTGSPTLAMFTQSIREVDTPDP   400
 401  ENLTTTASGDGEVPTSTDGDTEADSSPTGGPTLKPREEATLGSHGEEWLT   450
 451  PAVSKMPLKAFEEEEASGTAIDSLDVIFTPTVVLEQVSRRPTDIQATFTP   500
 501  TVVLEETSGAPTDTQDALTPTVAPEQMFTAEPTDGGDLVASTEEAEEEGS   550
 551  GSMPPSGPPLPTPTVTPKRQVTLVGVEAEGSGPVGGLDEGSGSGDIVGNE   600
 601  DLLRGPPGPPGPPGSPGIPGKPGTDVFMGPPGSPGEDGAPGEPGPQGPEG   650
 651  QPGLDGASGQQGMKGEKGARGPNGSAGEKGDPGNRGLPGPPGKNGEVGTP   700
 701  GVMGPPGPPGPPGPPGPGCTTELGFEIEGSGDVRLLSKPTISGPTSPSGP   750
 751  KGEKGEQGAKGERGADGTSTMGPPGPRGPPGHVEVLSSSLINITNGSMNF   800
 801  SDIPELMGPPGPDGVPGLPGFPGPRGPKGDTGVPGFPGLKGEQGEKGEPG   850
 851  AILTGDVPLEMMKGRKGEPGIHGAPGPMGPKGPPGHKGEFGLPGRPGRPG   900
 901  LNGLKGAKGDRGVTLPGPPGLPGPPGPPGPPGAVVNIKGAVFPIPARPHC   950
 951  KTPVGTAHPGDPELVTFHGVKGEKGSWGLPGSKGEKGDQGAQGPPGPPVD  1000
1001  PAYLRHFLNSLKGENEDASFRGESSNNLFVSGPPGLPGYPGLVGQKGEAV  1050
1051  VGPQGPPGIPGLPGPPGFGRPGVPGPPGPPGPPGPPAILGAAVALPGPPG  1100
1101  PPGQPGLPGSRNLVTALSDMGDMLQKAHLVIEGTFIYLRDSGEFFIRVRD  1150
1151  GWKKLQLGELIPIPADSPPPPALSSNPYQPQPPLNPILSANYERPVLHLV  1200
1201  ALNTPVAGDIRADFQCFQQARAAGLLSTFRAFLSSHLQDLSTVVRKAERF  1250
1251  GLPIVNLKGQVLFNNWDSIFSGDGGQFNTHIPIYSFDGRDVMTDPSWPQK  1300
1301  VVWHGSNPHGVRLVDKYCEAWRTTDMAVTGFASPLSTGKILDQKAYSCAN  1350
1351  RLIVLCIENSFMTDTRK                                   1367

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.