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

NucPred

Fetching P38904 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MAYDEDDGEINFNELVGNLLSSHNQEGQEEGEVQGGEQEGDDFEKIYPTS    50
  51  ENIEPKHPDDSQHMHNSPDQNIEIPHFVDEEDELVSVVANAVQNIDDEQA   100
 101  KPENHLENGSEHVTSDTADDNHEKEQQQEWAHILQQEILKSDGEPLRENT   150
 151  ERRVSTSQHHPSQRTDDALDQDDENLRMAILESLQELNTNEEEEKEPEKH   200
 201  EHAAPNDKLSSKKSSKKKKKDKSKNRESSKDKSSKKSKSSSHSKKHAKDR   250
 251  NKEKQSKPTNNENTLDLSNILENLIHENDNAAIDTAKQTVDIQDNSHTDN   300
 301  TNNEDVEAQALVEATLKAFENELLSSAPTEEPSQEQSIGPVSSRKAVEPP   350
 351  RKPTADDIPLAMLQAFKPKKRPPQEKKKTKSKTSKAASTANKSPASESTS   400
 401  KKKKKKKTVKESNKSQEAYEDDEFSRILADMVNQVVNTSLKETSTHTATQ   450
 451  DNKLESESDFTSPVQSQYTTEDASTANDDSLDLNQIMQNAMAMVFQNQND   500
 501  DEFDENIVEDFNRGLGDLSVSDLLPHDNLSRMEKKSVPKSSSKSEKKTAI   550
 551  SRRASKKASRDASSVELTEVPSKPKKPSKTEVSLEKKLRKKYVSIANEAA   600
 601  SVARKKRWAKNKELKEKEKLERQTAREERRHKKKLEKQRLAEEQEELKKI   650
 651  VERGPPYPPDLRLTKSGKPKKPYRRWTPEELLKRSQEAEKPRKVKKERKK   700
 701  KEKKMKVPSSALKKIPLFNFVKGNVQPSARHRLNDIEGSLSTIGLHKSPD   750
 751  GVRRILSRPKSEDHEWPLSDSSASQNYDAHLKTVVHKEKIPFHPPWTIPS   800
 801  QPPFALPVARRKKIPNIKKYRKRTNNSFRVSKEGTASTRNRILPAILLPI   850
 851  INTLKAAAKSQTAAGATPEEARKRLATIIQHAKSTVIRAALQARKNSMQA   900
 901  AHSKGTTTELATTASRMKNPLKMIPIFNTSRVKQQLDKQLPARSAGTEIS   950
 951  SSESPDKATPDPHSNSTIAGHTLKGVTTPIKIEDSDANVPPVSIAVSTIE  1000
1001  PSQDKLELTKRAESVEPVENNVETAKETQSVQEIKENVGTKASEEVTLTE  1050
1051  DKTNGDPKNEKRILIESPVEKTDKKKPGEKIATDLNEDASLSDKKDGDEK  1100
1101  STLHSDAAQLTGNEPDSVNTTTGKPKLIDVSLKPLNEAKPKIPIIFPLKR  1150
1151  PQIKPEVSVINLVQNLVNTKIPEIKNESVDLGSNITDILSSTITNILPEI  1200
1201  TATDVKNYQYEDENVKYLKKTPRQVLNLDGLVPPSGRCITKAKRVRRIKK  1250
1251  LSADATTAPEADGKANSESITYTFDIPSPEEVQSKRSVVLKFAKARLTEA  1300
1301  ELSCLKKEINNVRKRRWREMNSTKNWEYDVKSRLKKRANAFFGEGESETK  1350
1351  SKWIEERFQEKVSQEKYKDRLETTETQANNTKIVIDDKEILNILAVNMNN  1400
1401  LNKARCIEKDIQESFREEKLASLQPKKKRKKSILH                 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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