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

NucPred

Fetching P14046 from www.uniprot.org...

The NucPred score for your sequence is 0.30 (see score help below)

   1  MKKDREAQLCLFSALLAFLPFASLLNGNSKYMVLVPSQLYTETPEKICLH    50
  51  LYHLNETVTVTASLISQRGTRKLFDELVVDKDLFHCVSFTIPRLPSSEEE   100
 101  ESLDINIEGAKHKFSERRVVLVKNKESVVFVQTDKPMYKPGQSVKFRVVS   150
 151  MDKNLHPLNELFPLAYIEDPKMNRIMQWQDVKTENGLKQLSFSLSAEPIQ   200
 201  GPYKIVILKQSGVKEEHSFTVMEFVLPRFGVDVKVPNAISVYDEIINVTA   250
 251  CATYTYGKPVPGHVKISLCHGNPTFSSETKSGCKEEDSRLDNNGCSTQEV   300
 301  NITEFQLKENYLKMHQAFHVNATVTEEGTGSEFSGSGRIEVERTRNKFLF   350
 351  LKADSHFRHGIPFFVKVRLVDIKGDPIPNEQVLIKARDAGYTNATTTDQH   400
 401  GLAKFSIDTNGISDYSLNIKVYHKEESSCIHSSCTAERHAEAHHTAYAVY   450
 451  SLSKSYIYLDTEAGVLPCNQIHTVQAHFILKGQVLGVLQQIVFHYLVMAQ   500
 501  GSILQTGNHTHQVEPGESQVQGNFALEIPVEFSMVPVAKMLIYTILPDGE   550
 551  VIADSVKFQVEKCLRNKVHLSFSPSQSLPASQTHMRVTASPQSLCGLRAV   600
 601  DQSVLLQKPEAELSPSLIYDLPGMQDSNFIASSNDPFEDEDYCLMYQPIA   650
 651  REKDVYRYVRETGLMAFTNLKIKLPTYCNTDYDMVPLAVPAVALDSSTDR   700
 701  GMYESLPVVAVKSPLPQEPPRKDPPPKDPVIETIRNYFPETWIWDLVTVN   750
 751  SSGVTELEMTVPDTITEWKAGALCLSNDTGLGLSSVASFQAFQPFFVELT   800
 801  MPYSVIRGEAFTLKATVLNYLPTSLPMAVLLEASPDFTAVPVENNQDSYC   850
 851  LGANGRHTSSWLVTPKSLGNVNFSVSAEARQSPGPCGSEVATVPETGRKD   900
 901  TVVKVLIVEPEGIKKEHTFSSLLCASDAELSETLSLLLPPTVVKDSARAH   950
 951  FSVMGDILSSAIKNTQNLIQMPYGCGEQNMVLFAPNIYVLKYLNETQQLT  1000
1001  EKIKSKALGYLRAGYQRELNYKHKDGSYSAFGDHNGQGQGNTWLTAFVLK  1050
1051  SFAQARAFIFIDESHITDAFTWLSKQQKDSGCFRSSGSLLNNAMKGGVDD  1100
1101  EITLSAYITMALLESSLPDTDPVVSKALSCLESSWENIEQGGNGSFVYTK  1150
1151  ALMAYAFALAGNQEKRNEILKSLDKEAIKEDNSIHWERPQKPTKSEGYLY  1200
1201  TPQASSAEVEMSAYVVLARLTAQPAPSPEDLALSMGTIKWLTKQQNSYGG  1250
1251  FSSTQDTVVALDALSKYGAATFSKSQKTPSVTVQSSGSFSQKFQVDKSNR  1300
1301  LLLQQVSLPYIPGNYTVSVSGEGCVYAQTTLRYNVPLEKQQPAFALKVQT  1350
1351  VPLTCNNPKGQNSFQISLEISYMGSRPASNMVIADVKMLSGFIPLKPTVK  1400
1401  KLERLGHVSRTEVTTNNVLLYLDQVTNQTLSFSFIIQQDIPVKNLQPAIV  1450
1451  KVYDYYETDEVAFAEYSSPCSSDDQNV                         1477

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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