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

NucPred

Fetching Q2QLH6 from www.uniprot.org...

The NucPred score for your sequence is 0.50 (see score help below)

   1  MKASTVLAPGILALLFTLVQRSNGECKEALAMSKMNVDMKYQLPNFTAET    50
  51  PIQNIVLHEHHIYLGAINYIYVLDDKDLQKVAEYKTGPVLEHPDCFPCQD   100
 101  CSDKANLSGGIWKDNVNMALLVDTYYDDQLISCGSVNRGACQRHVLPRNN   150
 151  AADIQSKVHCMFSPQADEEPGQCPDCVVSALGAKVLLSEKDRFINFFVGN   200
 201  TINSSYFPNHPLHSISVRRLKETQDGFKFLTDQSYIDVLPEFRDSYPIKY   250
 251  VHAFESNHFIYFLTVQRETLDSQTFHTRIIRFCSVDSGLHSYMEMPLECI   300
 301  LTEKRRKRSTRKEVFNILQAAYVSKPGAHLAKQIGVSVNDDILFGVFAQS   350
 351  KPDSAEPMNRSAVCAFPIKYVNEFFNKIVNKNNVRCLQHFYGPNHEHCFN   400
 401  RTLLRNSSGCEVRSDEYRTEFTTALQRVDLFMGQFNQVLLTSISTFIKGD   450
 451  LTIANLGTSEGRFMQIMVSRSGSSTPHVNFHLDSHPVSPEVIVEHTVNQN   500
 501  GYTLVVTGKKISKIPLNGLGCEHFQSCSQCLSAPPFVQCGWCHDKCVRSE   550
 551  ECPSGSWTQETCRPAVHKVFPTSAPLEGGTRLTICGWDFGFRRNNKFDLK   600
 601  KTRVLLGNESCTLTLSESTTNTLKCTVGPAMNEHFNMSIVISNGRETTQY   650
 651  STFSYVDPVITSISPSYGPKAGGTLLTLIGKYLNSGNSRHISIGGKTCTL   700
 701  KSVSNSILECYTPAQIISTEFPVKLKIDLAIREASSFSYQEDPIVYEIHP   750
 751  MKSFVSGGSTITGVGKNLNSVSVPRMVIHVREAGRDFTVACQHRSNAEIL   800
 801  CCTTPSLQQLNLQLPLKTKAFFMLDGVLSKYFDLIYVHNPVFKPFEKPVM   850
 851  ISMGNENILEIKGNDIDPEAVKGEVLKVGNKSCENIHSRSEAVLCTVPND   900
 901  LLKLNSELNIEWKQAVSSTVLGKVIVQPDQNFTGLIVGVVSISIILLLLL   950
 951  GLFLWLKKRKQNKDPGSELVRYDARVHTPHLDRLVSARSVSPTTEMVSNE  1000
1001  SVDYRATFPEDQFPNSSQNGSCRQVQYPLTDLSPILTSGDSDISSPLLQN  1050
1051  TVHIDLSALNPELVQAVQHVVIGPSSLIVHFNEVIGRGHFGCVYHGTLLD  1100
1101  NDGKKIHCAVKSLNRITDIGEVSQFLTEGIIMKDFSHPNVLSLLGICLRS  1150
1151  EGSPLVVLPYMKHGDLRNFIRNETHNPTVKDLIGFGLQVAKGMKYLASKK  1200
1201  FVHRDLAARNCMLDENFTVKVADFGLARDMYDKEYYSVHNKTGAKLPVKW  1250
1251  MALESLQTQKFTTKSDVWSFGVLLWELMTRGAPPYPDVNTFDITVYLLQG  1300
1301  RRLLQPEYCPDPLYEVMLKCWHPKAEMRPSFSELVSRISAIFSTFIGEHY  1350
1351  VHVNATYVNVKCVAPYPSLLSSQDNIDGEVDT                    1382

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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