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

NucPred

Fetching P13508 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MRVLLILLAFFAPIASQLMGGECGREGACSVNGKCYNGKLIETYWCRCKK    50
51 GFGGAFCERECDLDCKRGEKCIYDVYGENPTCICQDCEDETPPTERTQKG 100
101 CEEGYGGPDCKTPLFSGVNPCDSDPCNNGLCYPFYGGFQCICNNGYGGSY 150
151 CEEGIDHCAQNECAEGSTCVNSVYNYYCDCPIGKSGRYCERTECALMGNI 200
201 CNHGRCIPNRDEDKNFRCVCDSGYEGEFCNKDKNECLIEETCVNNSTCFN 250
251 LHGDFTCTCKPGYAGKYCEEAIDMCKDYVCQNDGYCAHDSNQMPICYCEQ 300
301 GFTGQRCEIECPSGFGGIHCDLPLQRPHCSRSNGTCYNDGRCINGFCVCE 350
351 PDYIGDRCEINRKDFKFPDIQSCKYNPCVNNATCIDLKNSGYSCHCPLGF 400
401 YGLNCEQHLLCTPTTCANGGTCEGVNGVIRCNCPNGFSGDYCEIKDRQLC 450
451 SRHPCKNGGVCKNTGYCECQYGYTGPTCEEVLVIEKSKETVIRDLCEQRK 500
501 CMDLASNGICNPECNLEECNFDGGDCSGGQRPFSKCQYPARCADQFANGV 550
551 CNQECNNEECLYDGLDCQSELFRCPAHIRKHCIERRGDGVCNLECSFIGC 600
601 GFDGGDCNNGTEAIILSDIRIKVQIDPIEFQATGGETLMQISANLRATVR 650
651 IQRDELGPLVFRWDGEHEMERVEMNSSKLEDQFVLSHHVRRYRQAVVTGI 700
701 VLYLEVEEICKPEFCRFSTAQSVVDLIAAGLVKSDGRMSLGLPITEAMVA 750
751 VPKRNEIDEGWSRSQVILFACIAFLAFGTVVAGVIAKNGPERSRKRKMVN 800
801 ATVWMPPMESTNEKGRRNQSNHSSQCSLLDNSAYYHPNTKRHCSDYSTGY 850
851 NGEQYSQIYPQTLANGYPGDYNELNFDFQSETFAPADLPADEIPLHVQAA 900
901 GPDAITAPITNESVNQVDSKYRRRVLHWLAANVRGKPEDVITTEAIRCLK 950
951 AGADVNARDCDENTALMLAVRAHRVRLSVVLLREGANPTIFNNSERSALH 1000
1001 EAVVNKDLRILRHLLTDKRLLKEIDELDRNGMTALMLVARELGKHQVEMA 1050
1051 ELLLSKGAKLDYDGAARKDSNKYKGRTALHYAAMHDNEEMVIMLVRRSSN 1100
1101 KDKQDEDGRTPIMLAAKEGCEKTVQYLALNDASLGIVDSMDMTAAQVAEA 1150
1151 SYHHELAAFLRQVANERHRNDIMRQQIVKSGHGAKSGRQTVKNIKRAGSR 1200
1201 KTPTSAASSRETNHLTPPPSDGSFSSPSPHYYPTTTSTPNRMETSPEYMF 1250
1251 NHEMAPPVNAMWYTTPPPYQDPNYRHVPPNTAFQNAEQMNGSFYC 1295

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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