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

NucPred

Fetching Q08696 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MSLCRCSSICLRRPILRSFNFLNKYIDQSQHSGGLSSFQRLSFSNTGKNE    50
  51  STDDSNQIRCDADKTAADKKKQKQKEEEQAKIREYKRECLKVQKRVLAEE   100
 101  IRCSGEKDRILIQGMMKCLTDGMKKACTKIAKAKLIADKELAVQCAALSK   150
 151  KDKVKALLKKCEREKSKEKECNQNSPAEGDKDRTKKGKTKGKSGGGNKKR   200
 201  STKENRAKKGKKLVKNRFTQKLEHCIKSEWADVCECRQNFTEDERKRLAA   250
 251  SYKCMGTKIKSICRKRVIAEMCEAAGYVKSSEPKKKGKKKKNDEKKEKEL   300
 301  EREILKEQAEEEAKIRGVVKEVKKKCKEKALKKKCKDLGRKMKEEAEKKK   350
 351  CAALAKKQKEEDEKKACKELAKKKKEADEKKKCEEAANKEKKAAEKKKCE   400
 401  KAAKERKEAAEKKKCEEAAKKEKEAAERKKCEELAKNIKKAAEKKKCKEA   450
 451  AKKEKEAAERKKCEELAKKIKKAAEKKKCEETAKKGKEVAERKKCEELAK   500
 501  KIKKAEIKKKCKKLAKKEKETAEKKKCEKAAKKRKEAAEKKKCEKAAKKR   550
 551  KEAAEKKKCEKSAKKRKEAAEKKKCEKAAKERKEAAEKKKCEEAAKKEKE   600
 601  VAERKKCEELAKKIKKAAEKKKCKEAAKKEKEAAEREKCGELAKKIKKAA   650
 651  EKKKCKKLAKKEKETAEKKKCEKAAKKRKEAAEKKKCAEAAKKEKEAAEK   700
 701  KKCEEAAKKEKEAAERKKCEELAKKIKKAAEKKKCKKLAKKKKAGEKNKL   750
 751  KKGNKKGKKALKEKKKCRELAKKKAAEKKKCKEAAKKEKEAAEKKKCEKT   800
 801  AKKRKEEAEKKKCEKTAKKRKEAAEKKKCEKAAKKRKEEAEKKKCEKTAK   850
 851  KRKETAEKKKCEKAAKKRKQAAEKKKCEKAAKKRKEAAEKKKCAEAAKKE   900
 901  KELAEKKKCEEAAKKEKEVAERKKCEELAKKIKKAAEKKKCKKLAKKEKK   950
 951  AGEKNKLKKKAGKGKKKCKKLGKKSKRAAEKKKCAEAAKKEKEAATKKKC  1000
1001  EERAKKQKEAAEKKQCEERAKKLKEAAEQKQCEERAKKLKEAAEKKQCEE  1050
1051  RAKKLKEAAEQKQCEERAKKLKEAAEKKQCEERAKKEKEAAEKKQCEERA  1100
1101  KKLKEAAEKKQCEERAKKEKEAAEKKRCEEAAKREKEAAEKKKCAEAAKK  1150
1151  EKEATEKQKCAEAAKKEKEAAEKKKCAEAAKREKEAAQKKKCADLAKKEQ  1200
1201  EPAEMKKCEEAAKKEKEAAEKQKCAKAAKKEKEAAEKKKCAEAAKKEQEA  1250
1251  AEKKKCAEAAKKEKEAEKKRKCEKAEKAAALKRQCAKLVIRAKEAALRKK  1300
1301  CAIIAKKAKMAAEKKECEKLAKKAKEAIEWKKCAKLAKKKREAEKKKCAK  1350
1351  LAKKEKEAAEKKKRCKDLAKNKKKGHKKKGRNENRKKRTDC           1391

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.