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

NucPred

Fetching Q9SJQ6 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MEKQRREESSFQQPPWIPQTPMKPFSPICPYTVEDQYHSSQLEERRFVGN    50
  51  KDMSGLDHLSFGDLLALANTASLIFSGQTPIPTRNTEVMQKGTEEVESLS   100
 101  SVSNNVAEQILKTPEKPKRKKHRPKVRREAKPKREPKPRAPRKSVVTDGQ   150
 151  ESKTPKRKYVRKKVEVSKDQDATPVESSAAVETSTRPKRLCRRVLDFEAE   200
 201  NGENQTNGDIREAGEMESALQEKQLDSGNQELKDCLLSAPSTPKRKRSQG   250
 251  KRKGVQPKKNGSNLEEVDISMAQAAKRRQGPTCCDMNLSGIQYDEQCDYQ   300
 301  KMHWLYSPNLQQGGMRYDAICSKVFSGQQHNYVSAFHATCYSSTSQLSAN   350
 351  RVLTVEERREGIFQGRQESELNVLSDKIDTPIKKKTTGHARFRNLSSMNK   400
 401  LVEVPEHLTSGYCSKPQQNNKILVDTRVTVSKKKPTKSEKSQTKQKNLLP   450
 451  NLCRFPPSFTGLSPDELWKRRNSIETISELLRLLDINREHSETALVPYTM   500
 501  NSQIVLFGGGAGAIVPVTPVKKPRPRPKVDLDDETDRVWKLLLENINSEG   550
 551  VDGSDEQKAKWWEEERNVFRGRADSFIARMHLVQGDRRFTPWKGSVVDSV   600
 601  VGVFLTQNVSDHLSSSAFMSLASQFPVPFVPSSNFDAGTSSMPSIQITYL   650
 651  DSEETMSSPPDHNHSSVTLKNTQPDEEKDYVPSNETSRSSSEIAISAHES   700
 701  VDKTTDSKEYVDSDRKGSSVEVDKTDEKCRVLNLFPSEDSALTCQHSMVS   750
 751  DAPQNTERAGSSSEIDLEGEYRTSFMKLLQGVQVSLEDSNQVSPNMSPGD   800
 801  CSSEIKGFQSMKEPTKSSVDSSEPGCCSQQDGDVLSCQKPTLKEKGKKVL   850
 851  KEEKKAFDWDCLRREAQARAGIREKTRSTMDTVDWKAIRAADVKEVAETI   900
 901  KSRGMNHKLAERIQGFLDRLVNDHGSIDLEWLRDVPPDKAKEYLLSFNGL   950
 951  GLKSVECVRLLTLHHLAFPVDTNVGRIAVRLGWVPLQPLPESLQLHLLEM  1000
1001  YPMLESIQKYLWPRLCKLDQKTLYELHYQMITFGKVFCTKSKPNCNACPM  1050
1051  KGECRHFASAFASARLALPSTEKGMGTPDKNPLPLHLPEPFQREQGSEVV  1100
1101  QHSEPAKKVTCCEPIIEEPASPEPETAEVSIADIEEAFFEDPEEIPTIRL  1150
1151  NMDAFTSNLKKIMEHNKELQDGNMSSALVALTAETASLPMPKLKNISQLR  1200
1201  TEHRVYELPDEHPLLAQLEKREPDDPCSYLLAIWTPGETADSIQPSVSTC  1250
1251  IFQANGMLCDEETCFSCNSIKETRSQIVRGTILIPCRTAMRGSFPLNGTY  1300
1301  FQVNEVFADHASSLNPINVPRELIWELPRRTVYFGTSVPTIFKGLSTEKI  1350
1351  QACFWKGYVCVRGFDRKTRGPKPLIARLHFPASKLKGQQANLA         1393

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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