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

NucPred

Fetching O42350 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MLSFVDLRSVLLLAVTLYLVTCQEVRRGPRGDKGPPGEQGPPGIPGRDGE    50
  51  DGLPGLPGPPGVPGLGGNFAAQYDPSKSAEPGQQGIMGPRGPPGPPGSPG   100
 101  SQGFQGLPGENGEPGQTGPVGSRGPSGAPGKAGEDGHPGKSGRPGERGPV   150
 151  GPQGARGFPGTPGLPGFKGIRGHTGSDGQKGAPGAAGVKGENGANGDNGS   200
 201  PGQAGARGLPGERGRIGPAGSAGSRGSDGSSGPVGPAGPIGSAGAPGLPG   250
 251  APGAKGELGPAGNNGPTGAAGGRGEPGPPGSLGPAGPPGNPGTNGVNGAK   300
 301  GTAGLPGVGGAPGLPGGRGIPGPAGPAGPSGARGLAGDPGIAGGKGDTGS   350
 351  KGEPGSVGQQGPAGPSGEEGKRGPNGEAGSSGPSGNAGIRGVPGTRGLPG   400
 401  PDGRAGGIGPAGSRGSSGPPGARGPNGDAGRPGEPGLLGARGLPGFSGSN   450
 451  GPQGKEGPAGPQGIEGRSGAAGPAGARGEPGAIGFPGPKGPNGEPGKNGD   500
 501  KGNQGPSGNRGAPGPDGNNGAQGPAGLGGATGEKGEQGPSGAPGFQGLPG   550
 551  PGGPPGEVGKPGERGAPGDFGPPGSAGTRGERGAPGESGGAGPHGPSGSR   600
 601  GPSGAPGPDGQKGEPGAAGLNGGLGPSGPAGIPGERGTAGTPGTKGEKGD   650
 651  AGNSGDYGNPGRDGARGPAGAAGAPGPAGGPGDRGESGPAGPSGVAGPRG   700
 701  APGERGEAGPAGPTGFAGPPGAAGHTGAKGDRGAKGPKGEAGSPGPLGAH   750
 751  GSAGPAGPNGPAGSTGARGDAGPSGATGFPGPAGRAGAPGPPGNVGPSGP   800
 801  TGHPGKDGSRGPRGDSGPVGRPGEQGQHGPVGLAGDKGPSGEAGPAGPPG   850
 851  AAGPSGVLGARGILGLPGTRGERGLPGGPGSNGEPGPSGLAGSSGPRGPP   900
 901  GSVGSPGPVGHSGEAGRDGHPGNDGPPGRDGLPGAKGERGYPGNTGPSGL   950
 951  AGAPGPAGSAGPAGKSGNRGEGGPSGPAGITGPSGPRGPAGPQGVRGDKG  1000
1001  EAGERGARGLDGRKGHNGLSGLPGPSGTPGETGPSGSVGPVGPRGPSGPS  1050
1051  GPPGKEGRSGHPGAMGPVGPRGPAGFTGPAGPPGPPGPPGHAGPSGGGYD  1100
1101  GGDGGEYYRADQPERKPKDYEVDATLKSLNQQIEVILTPEGSRKNPARTC  1150
1151  RDLRLSHPEWTSGFYWIDPNQGCTSDAIRVFCDFSSGETCIHANPDEITQ  1200
1201  KNWYINTSNKDKKHLWFGEILNGGTQFEYHDEGLTAKDMATQLAFMRLLA  1250
1251  NQASQNITYHCKNSIAYMDEETGNLKKAVILQGSNDVELRAEGNTRFTYS  1300
1301  VLEDGCTKHTGEWGKTVIEYRTNKPSRLPILDIAPLDIGGHDQEIGFEIG  1350
1351  PVCFK                                               1355

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.)

Go back to the NucPred Home Page.