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

NucPred

Fetching Q10719 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MMTASFKGIRISKPIVKEISSFGSLTNIDLHTDPYEKVEAKALSRSRLKN    50
  51  QSVKKTDLRITNDYSSLFVSIENKKNTIPDIHCNNLSKRPVGFTDSYVPG   100
 101  EALLCPDDPNLVNELFDDVLKRLREEKSDSGEQFHWDANVTLSQENKWSF   150
 151  ITGYLSRNDKFLKISSNDSELNVKASVISYIEKLSCTPLKLKYVESLAVA   200
 201  LRTESVTWVRYFLLMGGHIVLAKILQAIHEKKHLKSPDITLEIAILKSMR   250
 251  CIIGQKIGTDFYLSNKYPIDSVVHCLLSTKLLVRKLAAELLTFLCYSEKP   300
 301  NGINAIMKCMKNFANLKVESMNVFDLWLSQWKRTLLEKVVTEEKKVLEEA   350
 351  ALHDKITIEYIISQMLLINAFLENIPSKTALLQFKESLRIGNFKSILLIL   400
 401  KKINDEGVLKQLEKCVKLVSLDTANEKHFLKHTPNSAAHQSLLNTNMFND   450
 451  ANFEFMVKEHIKNFLKLLKEHNNPVRIIKLLDCLVLTLQADKGNGNSNND   500
 501  IDCFYKELKIGNEQGNNAPGYSSVTSGYGTTNSKKVVASYDNTDDNEYSV   550
 551  SKSELYATGDTNNTTNQGYENSERKYVESSKYETDLKNIFDCLCLLFPSE   600
 601  FDPQSSFSAEKIFSKLKHLLTRTRDSYISEDTKILRLLNRSSSKLQDRDQ   650
 651  EYLISKNNVNGNGNRDWVQPVNTTSSVSAFASPRIKPKLLFQPNQDEKLK   700
 701  LCKLDLAKANSITLKSEPSSAVSTHSFEVHLSMPGTQIKSANLAEKMETS   750
 751  KHKVFNPKRIDVVSDLPLDYRKSYYGRFSITDTKRFSKIENMRIKEVIDG   800
 801  NPFKAPPPAPLPPPAPPLPTAMSSLQKFEKNDSQIFRKTIIIPENISIDD   850
 851  IFKFCSGSESEVYASKIPGELCNPSKRLKQLHWKRLEVPFEKTLWNIVVA   900
 901  DPYLLTLKLTAEGIFKQLEDCYPLREVTVSNKKVKEYTGFMPVDLQQMVS   950
 951  IRLHRFNSLTPIEIAKKFFHCDHDIMELVDFFNDRKFFRQEGLKKQLKPY  1000
1001  MSSRNEEVMEVSEKLLELSRFDQIYTLIVVDIDTYYEKRMAALKIKSFLA  1050
1051  NNFRDFRRQIRKLHCASLELKSSLHFKYFLNLVLHIGNFMNDAPRRAKGY  1100
1101  RLESLLRASMIKNDKTGLTLLHTIEKIVRTHFPQLEAFLVDLKAIPEISR  1150
1151  FNLEQLEQDCNDICERMKNVEKDFSNEGIFSNHKALHPDDHICEVMVPWI  1200
1201  PSGKSMVDELNSDITELKTTLKTTLLMYGENPDEPTSSARFFNNLNEIIL  1250
1251  EYKKASTVNQKMEKEEELAFLRLQALKASVKSNNAENSGSSKNEEVSATM  1300
1301  ENLISQLQKGLCDDSLSNKTDCTESSKQTIETLMNYENDKQTLEGSNKKR  1350
1351  QTVVLKAECMLKQLENNNELKR                              1372

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.)

Go back to the NucPred Home Page.