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

NucPred

Fetching P34675 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MSETQEQEASGNGEPDLPTTIRVTLKTLDDREATVTIGLQDTIQSLIDLG    50
  51  RREMNIQSGFQRVIAGGRVLNSTQTVQAAGISDGQTVHLVDRGPSGENDR   100
 101  PNVMPDRVAGPRIINAIPGLPPPGFIFQSPAFARMIPGNVEIPTPPSQTQ   150
 151  HTVVHPIRVPGSIAGTPVLTSRVSEDCVLQKAVPYRGTSNSPNRPQAASQ   200
 201  TVTFPSEPNVIQWTVNIADDLIFRPREHFEQVVRETINNISFLSDSTRLG   250
 251  VSMKWNQNCTSLSVELPPVSPHIPSPALEKLDFLCLWTDHLSRFIDKLEE   300
 301  HDGLVAATRHVLEMVKTRQFDQNLSQQARNQRVEALDEIVKHLEYQWAEL   350
 351  SHMKDFERIRFRKNQTEEYRALKIQEYPETPRNPHFYMRHALDIDVIGVM   400
 401  REFRKQQRRFTRLEDLLDDLNEVGAVKFIRDHITTEVDYRYQALSMFYCY   450
 451  IQRMRHQISHMTHLTADLDVSFITPSFPQRILPQYAFQSSDEQPLTIPVT   500
 501  HIFEPPRMLSDVGGRYNGDYPYLAYHPPSVHMEVVLQEPRRIAEPRPQIL   550
 551  ARPTPQQFVLTQEMNQGGSINLMAATDPISGLSLQDVLRAQQEQVENLFA   600
 601  QQPGIEGGRVRVTARPGRRFVATTGDAPSVPVETLPPPGSDQQPGTSRRF   650
 651  TTHRFNVQPDARGAETETLAPFPVAIEPNELQRIAKNIASRYRAEALQRI   700
 701  ASSLTTRFNNESWDTRIQNMPLCTLRECVAIALEMLTSAGNTVNESKDLM   750
 751  LALVRDEEVLVRAIAECIKSLFGRGEFPTHVARLIMPTNQTASSRNDYES   800
 801  VDGVEESQSDEFDSMIVRVPSDISQPQSGDLRAIRERRQNRRQFLENRGR   850
 851  IPSTSSAPSTSENPPGPSFNSEDAADIRAGRLPLGTRPNRRTVRETVHPA   900
 901  AAARAESPNHISLTFTATTHTFAPAGFPLMMASSNVPSTSAGPPGWPIRQ   950
 951  VVSPTPTTRGLFEFDLSGSSDQPARSTPSPPAPTPRTTSAPATVQSSPTR  1000
1001  QESMDIDSPNVQNPGHVESPAAIAARQAARVARARIDHLAATFNGDLADS  1050
1051  RRQSPFVTPGPTTPLNDPRRRTVRVTQHVKPMVAIDPFMNCTNRHCEINR  1100
1101  LATPTHMADGDRFTLQSLQPDQEFEARIQALVPSIERRPIQIHHEDEDYN  1150
1151  YSIRRTQSGLLSFRNLEDFRPFVKTAIRSLLAHCIDADTLFTMNMNNISG  1200
1201  YQAANHTELLRMVKEHISRVPGSRATRNASQNTTSVNQSTETSPREQMNR  1250
1251  SPVQEAADPRLAFSPFPPGINLEQEVLIPGQIASLLTYLVDYMESSSNPR  1300
1301  PPGIFGFLLELTYGRLTRHDFAQLARRTTATNVASEFEAQIRAHIRDNYL  1350
1351  VGRTGLSNSELHGIAENLANNEQFFAIFMSQNDQLPTSFPFGYDRNDFAE  1400
1401  VVWAFRQIEIALIKSFLTLSQLNLDSGNAVRFILQSVDSYLYRNLIMFYR  1450
1451  MCDRDVERMKIQMKRISDYFATIRYESTDRPGINVFIDNWNRVMDYWSNR  1500
1501  YTDFSEENFDQFLLKVRAGTDWNDIVLNESRQLLPTIASTSSQPSTSSSS  1550
1551  LNTVSTNNPRKRNHDGSREDNDDCVDVVAPMMTSLSTSSPLTSQSSSSGT  1600
1601  RTSSGSSGPSTSSTTTNNIQ                                1620

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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