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

NucPred

Fetching P49468 from www.uniprot.org...

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

   1  MKTYTYQNTLISKKQLKQLLSWSFTTYDSMQACSLADELKYLGFKYASKA    50
  51  GISISIEDLKVPYNKNLLLKIAHQEINSSEKIYLKGKLTDVERFQKLIDT   100
 101  WNLTSESLKDELVSYFKRYDPLNSVYIMAFSGARGNLSQVRQLVGMRGLM   150
 151  SDPSGELLKLPIKKNFREGLTITDYLMSGYGARKGIIDTALKTANSGYLT   200
 201  RRLIDVAQDIIIREKDCLTKHSCLIINFESNLRIKKSVYEKILGRLLNKS   250
 251  IYDEKTKELIAEVNTQVTPNLIRTLKQKQIKHFYVRSPLTCSLYRSICQK   300
 301  CYGWDLANENLIDIGERIGIIAGQSIGEPGTQLTMRTFHTGGIFTSEIRG   350
 351  TIRSPISGIVKFSKRLKRIPIRTNRGEDVLLTKNAGSLIIIPEEKNSKPV   400
 401  KLELFRNTVVFHKNNQYIQKNAIIAELVDDEKQTRTEIKPVLTTTSGEVF   450
 451  IPRIINKLDNINKTKLLWILSGNVYQAPQHSFLNFYNDYKINKNSYIFRT   500
 501  KLINDFSGFTVFTNSKYNLFQRILQLVSNSCWILPNSKIQKLQSSLNKKP   550
 551  YFLNIKKLKYLIDLKLLNSKYFIEISSNKHFGTLVTNNYQTLTGGIGYYD   600
 601  FRCRDRIISDNKTISYFLPWEPKKKSISLEFLTLLESQFLKSFDILSLIL   650
 651  KKNPDLEDCRLAFFPNNFNLHSKVETFSHYSKQTNSLNLAWFSIVKQFPY   700
 701  RSVIWMSEENYELNCDKNLLLVEHGNFISKNFEIVPGIVSKTGGIVMISD   750
 751  KNKLTQEITIKTGSVYEGSLFNYFKNKIFYPGEIILDSLKITQPSFCECF   800
 801  EGRFNDQLLIRPLQVYEVPQFKSLIQIFGTKFQTDLPFNLTNNISYRCKS   850
 851  NKIIKESRNFTIIDNILDVNIRTFAKKQFEIELFSDVKKNHLNFLVSEKL   900
 901  SLNHFILPQLRYTDIQSCLLVQTHQFIDSYTILGYLEVMISKSLEIVQFK   950
 951  SKYKDSKQICLISNEDCRTIPKNSVKNKTIDNLLINNANVNYTGKILMDN  1000
1001  DEFVTIQKGRPYFFPNCKNEEAIINTDLIYKPLQSSSFLDNSKLKTNRLV  1050
1051  YLNYFDITKGLINQRIHSQDIICKFSKMFIKKNGKLYSSLLAGLINRIAI  1100
1101  INKQLDSQQIPSCPTSIRKYREENSSKKLKKRMKRKYKKITGIKTLLFIK  1150
1151  NSELNLNPLKDTQDRKNSLTVATFMLSKFYKFTGGIHSITEDYFDEEVNS  1200
1201  VFCKNGEFVKNGQTIGLLNFEKEITGDIVQGLPRVEQLLEARKKKQITKN  1250
1251  LPINKKKGLLTQTTSIDSYFEFKKLGTSIKENEKINPHNLLKVYFNYYGL  1300
1301  IKTFFCENSYTKDSYRLFNNYEASYRSFKKVQSLILNSVQSVYKSQGVSI  1350
1351  ADKHLEVIIKQMTTKVLITHQGNTSLLPREVIDLYHIEYINKIARIHKKH  1400
1401  PALYVPLLLGITKAALNNPSFISAASFQETTRVLTKAAIEGRVDWLRGLK  1450
1451  ENIIIGHLMPAGTGSPVYTNCFKKSFENNLN                     1481

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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