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

NucPred

Fetching Q42510 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MGRLKLHSGIKAIEEEPEDFECTDSSNTTTLACMIDTEIAAVLAVMRRNV    50
  51  RWGGRYMSGDDQLEHSLIQSLKALRKQVFSWNQPWHTISPMLYLQPFLDV   100
 101  IRSDETGAPITSIALSSVYKILNLNVIDQNTANIEDAMHLVVDSVTSCRF   150
 151  EVTDPASEEVVLMKILQVLLACMKNKASVMLSNQHVCTVVNTCFRVVHQA   200
 201  GMKGELLQRVARHTMHELVRCIFSHLPDVERTETTLVNRAGSIKQEKAGV   250
 251  DSDYAIVSKPVEDGNANSEYDVENSMATFATGAQSLMDDGPVGPGSRKPA   300
 301  SPYDLHIMTEPYGVPSMVEIFHFLCSLLNVVEHVGMGSRSNTIAFDEDVP   350
 351  LFALNLINSAIELGGSSIRHHPRLLSLIQDELFRNLMQFGLSMSPLILSM   400
 401  VCSIVLNLYQHLRTELKLQLEAFFSCVILRLAQGKYGPSYQQQEVAMEAL   450
 451  VNFCRQKSFMVEMYANLDCDITCSNVFEELSNLLSKSTFPVNCPLSAMHI   500
 501  LALDGLIAVIQGMAERISNGLTGLDLGPVHLDEYTPFWMVKCDNYSDPNH   550
 551  WVSFVRRRKYIKRRLMIGADHFNRDPKKGLEFLQGTHLLPDKLDPQSVAC   600
 601  FFRYTAGLDKNLVGDFLGNHDEFCVQVLNEFAGTFDFQYMNLDTALRLFL   650
 651  ETFRLPGESQKIQRVLEAFSERYYMQSPEILANKDAALVLSYSIIMLNTD   700
 701  QHNVQVKKKMTEEDFIRNNRHINGGNDLPREFLSELFHSICNNEIRTTPE   750
 751  QGAGFPEMTPSRWIDLMHKSKKTAPYILADSRAYLDHDMFAIMSGPTIAA   800
 801  ISVVFDHAEHEDVYQTCIDGFLAIAKISACHHLEDVLDDLVVSLCKFTTL   850
 851  LNPSSVDEPVLAFGDDAKARMATITIFTIANKYGDYIRTGWRNILDCILR   900
 901  LHKLGLLPARVASDAADESEHSSEQGQGKPLANSLSSAHLQSMGTPRRSS   950
 951  GLMGRFSQLLSLDTEEPRSQPTEQQLAAHQRTLQTIQKCHIDSIFTESKF  1000
1001  LQAESLLQLARALIWAAGRPQKGTSSPEDEDTAVFCLELLIAITLNNRDR  1050
1051  IVLLWQGVYEHIATIAQSTVMPCNLVDKAIFGLLRICQRLLPYKESLADE  1100
1101  LLRSLQLVLKLDARVADAYCEQIAIEVSRLVKANANHIRSQAGWRTITSL  1150
1151  LSITARHPEASESGFDAVSFVMSEGTHLYPANYVLCVDAARQFAESRVGQ  1200
1201  SERSIRALDLMGDSLEFLAKWALSAKENMGEEDFGKMSQDIGEMWLRLVQ  1250
1251  GLRKVCLDQREDVRNHALQSLQKCLGGVDGINLAHSMWSQCFDKVIFTVL  1300
1301  DDLLEIAAGSQKDYRNMEGTLLLAIKLLSKVFLQQLQELSQLSTFCKLWL  1350
1351  GVLTRMEKYMKVKVRGKKSDKLQESVPELLKNILLVMKTKGVLLQRSALG  1400
1401  GDSLWELTWLHVNNIAPSMRLELFPDQESSQLGDDETVSNGLSSPENTTG  1450
1451  S                                                   1451

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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