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

NucPred

Fetching P54675 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MRQIVTGVIHQTTQSQQIPNVINSNQIQFSNEPMVVGSIEDFDIDSEVPP    50
  51  LAINLQRSINNNNNNNNNNNNNNNNNNNNNNNNNNNNTQPCTTVFLDRDS   100
 101  CVNVKATIDLLKEQLEFTIKDLIDFKENYDKLESTEQFKQWSNLIKNIKE   150
 151  NSLNNSNIYLTIPTTQNLINNNNNNNNNNNNNNNNNNNNNNNNNNNVIIP   200
 201  SASTENKEENDNNNSNNNNNINLSPDSSITKDINITENKITEIKTTETKE   250
 251  TSTGTSPLEKSPSKGFIISPKKPEEENEIEGETINNIAITNYTQGPSMLT   300
 301  LMKKKLENIKKNNNNNNNNGNGNNNSNNNNSNSNNNNNGISPSSSPPSHL   350
 351  NGNNNNNNSNNTNSNNTTNATTNSVGFSITMTNSNSLSVSKRMNKFKSWT   400
 401  SSKPTSSSIGFASSPQNNGKPLNISGSSRFFTSRQDSKIDLLKSPSSSPP   450
 451  TQSDIFNENNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNEELINNNNNN   500
 501  NNDENYKIEETEESLKELLEKEKLENEEREKILKERNEIDNLKKKNHLSK   550
 551  GYFMRACNASNDDGLEEEDIPLQDEHWETNVIVLLPCRHHVKVPGSSSSS   600
 601  IDSIRQLAWASGKMQGHLNLEKDEKFFTLRWCNKDVVFDQDTPLGHLIQY   650
 651  NLNYNNPTQKPTNIKLELVLEDELCKERLVDLQSLEINNGRPSIWKSHID   700
 701  DVLSFNRKLRELAMLAKPQSNVPAARLTPYPPPKTIPEFFVIRVHLFKNQ   750
 751  TKSLRCANNHTAFSLMTILSEKLKNTTPFDPTQYRFLITGINQYVDPNVP   800
 801  LLSVEYIVEKIKRKGEIDLTMVELLSLGLIIQQQQQQQQQQQQQQQQQQI   850
 851  ENIDDENILKLNNGILNVLSKIEKPIREKDNCISSLTVTENLQVRLLHAH   900
 901  EIFASKASEIIGTDSPSIQLFIEAAVYFGGELLATQSSKLVSFQDTVVWN   950
 951  EWVNIPLAVSNIPNGARMCLGLNARYRGDIFNIGWVGHRLFDSKGILNTF  1000
1001  APFSLLLWPGKINPIGTCVDNLESKDQAIIIAFEFKDYVVPKTIHYEDDL  1050
1051  IELISKDENGNELPVVTMEEMDRVEQIILQDPLYSLNKEERLLIWKSRYF  1100
1101  CHTKPQALSKLLQSVEWTNYKQVGEAFQLLKIWPTLSAVDALELLDPKFA  1150
1151  DCVEIREYAVKCLDQMSDYELEIYMLQLVQAIKHDVFHNSVLSLFLIGRV  1200
1201  WQNMQVLGHPFFWHLRADIDNQEVCERFRVLSSGFLRYAPTQLMESFKRE  1250
1251  ITTLRILENLAKRVKEVPYEKRKQYVENNLREEQSFPTELFVPFDPSIRI  1300
1301  LNIIPEKCKSMDSAKVPLWVTFKNADPFAPPLQMIAKTGDDLRQDILTLQ  1350
1351  LLRLMDHMWKSQDLDLHMTIYRCIATGMGTGLIEVVPNSETAARIQAGAG  1400
1401  GVSGAFKQTPIANWLKNHNQTENSYQKAVSKFTLSCAGYCVATYVLGIGD  1450
1451  RHNDNIMVDIHGHLFHIDFGHFLGNFKTFAGFQREKAPFVLTPDFVYVIG  1500
1501  GKDSPNFAFFVDICCKAFNIIRSNAHVFINMFELMLSTGIPELRSENDIV  1550
1551  YLRDKFRLDLTDAEASEYFKKLIHESIGTLTTTINFAIHIMAHRKNLVSG  1600
1601  NSAPKIGSASSLNLNKNKPSSQSKLDLSRSDLSRSDSSRSDSSRLDLSRS  1650
1651  DKKNNKDNKEKEKEKEKEKEKENNDNNDKDNNNNSNNDTEKENSIDK     1697

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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