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

NucPred

Fetching P04157 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MYLWLKLLAFSLALLGPEVFVTGQGTTDDGLDTTEIVLLPQTDPLPARTT    50
  51  EFTPPSISERGNGSSETTYLPGFSSTLMPHLTPQPDSQTPSARGADTQTL   100
 101  SSQADLTTLTAAPSGETDPPGVPEESTVPETFPGGTPILARNSTAPSPTH   150
 151  TSNVSTTDISSGANLTTPAPSTLGFASNTTTSTEIATPQTKPSCDEKFGN   200
 201  VTVRYIYDDSSKNFNANLEGDKKPKCEYTDCEKELKNLPECSQKNVTLSN   250
 251  GSCTPDKIINLDVPPGTHNFNLTNCTPDIEANTSICLEWKIKNKFTCDIQ   300
 301  KISYNFRCTPEMKTFALDKHGTLWLHNLTVRTNYTCAAEVLYNNVILLKQ   350
 351  DRRVQTDFGTPEMLPHVQCKNSTNSTTLVSWAEPASKHHGYILCYKKTPS   400
 401  EKCENLANDVNSFEVKNLRPYTEYTVSLFAYVIGRVQRNGPAKDCNFRTK   450
 451  AARPGKVNGMKTSRASDNSINVTCNSPYEINGPEARYILEVKSGGSLVKT   500
 501  FNQSTCKFVVDNLYYSTDYEFLVYFYNGEYLGDPEIKPQSTSYNSKALII   550
 551  FLVFLIIVTSIALLVVLYKIYDLRKKRSSNLDEQQELVERDEEKQLINVD   600
 601  PIHSDLLLETYKRKIADEGRLFLAEFQSIPRVFSKFPIKDARKSQNQNKN   650
 651  RYVDILPYDYNRVELSEINGDAGSTYINASYIDGFKEPRKYIAAQGPRDE   700
 701  TVDDFWKMIWEQKATVIVMVTRCEEGNRNKCAEYWPCMEEGTRTFRDVVV   750
 751  TINDHKRCPDYIIQKLSIAHKKEKATGREVTHIQFTSWPDHGVPEDPHLL   800
 801  LKLRRRVNAFSNFFSGPIVVHCSAGVGRTGTYIGIDAMLESLEAEGKVDV   850
 851  YGYVVNLRRQRCLMVQVEAQYILIHQALVEYNQFGETEVNLSELHSCLQN   900
 901  LKKRDPPSDPSPLEAEYQRLPSYRSWRTQHIGNQEENKKKNRSSNVVPYD   950
 951  FNRVPLKHELEMSKESEAESDESSDEDSDSEETSKYINASFVMSYWKPEM  1000
1001  MIAAQGPLKETIGDFWQMIFQRKVKVIVMLTELMSGDQEVCAQYWGEGKQ  1050
1051  TYGDMEVMLKDTNKSSAYILRAFELRHSKRKEPRTVYQYQCTTWKGEELP  1100
1101  AEPKDLVTLIQNIKQKLPKSGSEGMKYHKHASILVHCRDGSQQTGLFCAL  1150
1151  FNLLESAETEDVVDVFQVVKSLRKARPGMVGSFEQYQFLYDIMASIYPTQ  1200
1201  NGQVKKANSQDKIEFHNEVDGAKQDANCVQPADPLNKAQEDSKEVGASEP  1250
1251  ASGSEEPEHSANGPMSPALTPSS                             1273

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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