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

NucPred

Fetching P19214 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MKCNISIYFFASFFVLYFAKARNEYDIKENEKFLDVYKEKFNELDKKKYG    50
  51  NVQKTDKKIFTFIENKLDILNNSKFNKRWKSYGTPDNIDKNMSLINKHNN   100
 101  EEMFNNNYQSFLSTSSLIKQNKYVPINAVRVSRILSFLDSRINNGRNTSS   150
 151  NNEVLSNCREKRKGMKWDCKKKNDRSNYVCIPDRRIQLCIVNLSIIKTYT   200
 201  KETMKDHFIEASKKESQLLLKKNDNKYNSKFCNDLKNSFLDYGHLAMGND   250
 251  MDFGGYSTKAENKIQEVFKGAHGEISEHKIKNFRKEWWNEFREKLWEAML   300
 301  SEHKNNINNCKNIPQEELQITQWIKEWHGEFLLERDNRSKLPKSKCKNNT   350
 351  LYEACEKECIDPCMKYRDWIIRSKFEWHTLSKEYETQKVPKENAENYLIK   400
 401  ISENKNDAKVSLLLNNCDAEYSKYCDCKHTTTLVKSVLNGNDNTIKEKRE   450
 451  HIDLDDFSKFGCDKNSVDTNTKVWECKNPYILSTKDVCVPPRRQELCLGN   500
 501  IDRIYDKNLLMIKEHILAIAIYESRILKRKYKNKDDKEVCKIINKTFADI   550
 551  RDIIGGTDYWNDLSNRKLVGKINTNSKYVHRNKKNDKLFRDEWWKVIKKD   600
 601  VWNVISWVFKDKTVCKEDDIENIPQFFRWFSEWGDDYCQDKTKMIETLKV   650
 651  ECKEKPCEDDNCKSKCNSYKEWISKKKEEYNKQAKQYQEYQKGNNYKMYS   700
 701  EFKSIKPEVYLKKYSEKCSNLNFEDEFKEELHSDYKNKCTMCPEVKDVPI   750
 751  SIIRNNEQTSQEAVPEENTEIAHRTETPSISEGPKGNEQKERDDDSLSKI   800
 801  SVSPENSRPETDAKDTSNLLKLKGDVDISMPKAVIGSSPNDNINVTEQGD   850
 851  NISGVNSKPLSDDVRPDKKELEDQNSDESEETVVNHISKSPSINNGDDSG   900
 901  SGSATVSESSSSNTGLSIDDDRNGDTFVRTQDTANTEDVIRKENADKDED   950
 951  EKGADEERHSTSESLSSPEEKMLTDNEGGNSLNHEEVKEHTSNSDNVQQS  1000
1001  GGIVNMNVEKELKDTLENPSSSLDEGKAHEELSEPNLSSDQDMSNTPGPL  1050
1051  DNTSEETTERISNNEYKVNEREDERTLTKEYEDIVLKSHMNRESDDGELY  1100
1101  DENSDLSTVNDESEDAEAKMKGNDTSEMSHNSSQHIESDQQKNDMKTVGD  1150
1151  LGTTHVQNEISVPVTGEIDEKLRESKESKIHKAEEERLSHTDIHKINPED  1200
1201  RNSNTLHLKDIRNEENERHLTNQNINISQERDLQKHGFHTMNNLHGDGVS  1250
1251  ERSQINHSHHGNRQDRGGNSGNVLNMRSNNNNFNNIPSRYNLYDKKLDLD  1300
1301  LYENRNDSTTKELIKKLAEINKCENEISVKYCDHMIHEEIPLKTCTKEKT  1350
1351  RNLCCAVSDYCMSYFTYDSEEYYNCTKREFDDPSYTCFRKEAFSSMIFKF  1400
1401  LITNKIYYYFYTYKTAKVTIKKINFSLIFFFFFSF                 1435

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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