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 0.87 (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  IQRMRHQISHMTHLTADLDVSFITPSFPQRILPQYAVNVLTVPFPHPATV   500
 501  IFKFQSSDEQPLTIPVTHIFEPPRMLSDVGGRYNGDYPYLAYHPPSVHME   550
 551  VVLQEPRRIAEPRPQILARPTPQQFVLTQEMNQGGSINLMAATDPISGLS   600
 601  LQDVLRAQQEQVENLFAQQPGIEGGRVRVTARPGRRFVATTGDAPSVPVE   650
 651  TLPPPGSDQQPGTSRRFTTHRFNVQPDARGAETETLAPFPVAIEPNELQR   700
 701  IAKNIASRYRAEALQRIASSLTTRFNNESWDTRIQNMPLCTLRECVAIAL   750
 751  EMLTSAGNTVNESKDLMLALVRDEEVLVRAIAECIKSLFGRGEFPTHVAR   800
 801  LIMPTNQTASSRNDYESVDGVEESQSDEFDSMIVRVPSDISQPQSGDLRA   850
 851  IRERRQNRRQFLENRGRIPSTSSAPSTSENPPGPSFNSEDAADIRAGRLP   900
 901  LGTRPNRRTVRETVHPAAAARAESPNHISLTFTATTHTFAPAGFPLMMAS   950
 951  SNVPSTSAGPPGWPIRQVVSPTPTTRGLFEFDLSGSSDQPARSTPSPPAP  1000
1001  TPRTTSAPATVQSSPTRQESMDIDSPNVQNPGHVESPAAIAARQAARVAR  1050
1051  ARIDHLAATFNGDLADSRRQSPFVTPGPTTPLNDPRRRTVRVTQHVKPMV  1100
1101  AIDPFMNCTNRHCEINRLATPTHMADGDRFTLQSLQPDQEFEARIQALVP  1150
1151  SIERRPIQIHHEDEDYNYSIRRTQSGLLSFRNLEDFRPFVKTAIRSLLAH  1200
1201  CIDADTLFTMNMNNISGYQAANHTELLRMVKEHISRVPGSRATRNASQNT  1250
1251  TSVNQSTETSPREQMNRSPVQEAADPRLAFSPFPPGINLEQEVLIPGQIA  1300
1301  SLLTYLVDYMESSSNPRPPGIFGFLLELTYGRLTRHDFAQLARRTTATNV  1350
1351  ASEFEAQIRAHIRDNYLVGRTGLSNSELHGIAENLANNEQFFAIFMSQND  1400
1401  QLPTSFPFGYDRNDFAEVVWAFRQIEIALIKSFLTLSQLNLDSGNAVRFI  1450
1451  LQSVDSYLYRNLIMFYRMCDRDVERMKIQMKRISDYFATIRYESTDRPGI  1500
1501  NVFIDNWNRVMDYWSNRYTDFSEENFDQFLLKVRAGTDWNDIVLNESRQL  1550
1551  LPTIASTSSQPSTSSSSLNTVSTNNPRKRNHDGSREDNDDCVDVVAPMMT  1600
1601  SLSTSSPLTSQSSSSGTRTSSGSSGPSTSSTTTNNIQ               1637

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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