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

NucPred

Fetching Q9NHE5 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MIDPSSSEEEGEDDAVPNVSSKGRLTNTTKGTSAVSIIGGSAGSVVGSNI    50
  51  PVSGSNTDLIGNQRQSNISSICNRNDVGNISVAALGSTSNKIEQICGNRA   100
 101  DTGNLEVPSNGIPSGISQETLNQSVGSSRANSLPRPLSPSPSLTSEKHET   150
 151  AEPHGKHEREEEERKRRIQLYVFISRCISYPFNAKQPTDMTKRQTKISKQ   200
 201  QLEIITQRFQAFLKGETQIMADEAFQNAVQSYHDVFLKSERVLKMVQSGA   250
 251  SSQHDFREVFRNNIEKRVRSLPEIDGLSKETVLTSWMAKFDIILKGTGEE   300
 301  DSKRPSRMQQSLNSELILSKEQLYDMFQQILLVKKFEHQILFNALMLDSA   350
 351  DEQAAAIRRELDGRMQRVGEMEKNRKLMPKFVLKEMESLYVEELKSSINL   400
 401  LMANLESLPVSKGNMDSKYGLQKLKRYNHSTPSFLKLILRSHGSLSKLEG   450
 451  DSEDGSTQLTKLDVVLTFQLEVIVMEVENGEKLQTDQAEASKPMWDTQGD   500
 501  FTTTHPLPVVKVKLYTENPGMLALEDKELGKVTLKPTPLSSKSPEWHRMI   550
 551  VPKNLPDQDIRIKIACRLDKPLNMKHCGYLYAIGKSVWKKWKRRYFVLVQ   600
 601  VSQYTFAMCSYKEKKSEPSEMMQLDGYTVDYIEAASANLMFGIDLNGGRY   650
 651  FFNAVREGDSISFACDDENECSLWVMAMYRATGQSHKPTPPITQDKNSAM   700
 701  SKIQGDADKARKHGMEDFISTDPCTFDHATLFKTLQNLTLEYRLNDPYAS   750
 751  LGWFSPGQVFVLDEYCARYGVRGCYRHLCYLSDLLDRAEKQHMIDPTLIH   800
 801  YSFAFCASHVHGNRPDGVGSITHEEKEKFSEIKERLRQLLEFQITNFRYC   850
 851  FPFGRPEGALKATLSLLERVLMKDIVTPVPPEEVRQMIKKSLETAALVNY   900
 901  TRLSNKAKIDEDLRGDVIVPAPKKLEDLIHLAELCVDLLQQNEEHYGEAF   950
 951  AWFSDLLVEHAEIFWSLFAVDMDRVLSEQAPDTWDSFPLFQILNDYLRTD  1000
1001  DNLRNGRFHQHLRDTFAPLVVRYVDLMESSIAQSIHKGFEKERWESKGIN  1050
1051  AALNPAALNNAAQALNTAALNPSMILCGKKDQVNFYVPKLPKQSNSTAAN  1100
1101  DEMRNGCATSEDLFWKLDALQSFIRDLHWPDAEFRQHLEQRLKMMAVDMI  1150
1151  EQCIQRTDSSFQSWLKKNIAFISTDYILPSEMCAMVNVILDAKNQSFKLT  1200
1201  TIDGIDLYKFHAKIDDQIDKANVAMTQGLSGKLMSVLESTLSKLARYDEG  1250
1251  SLIGSILSFTNVSSSGKDLGQGYVNFFRNNMDQVRGKIADDLWTLHFFEQ  1300
1301  WYSQQINMLCNWLSERVDHALHYAQVASISHIIKKIYSDFELQGVLEDKL  1350
1351  NSKAYQAVAQRMATEEATCALTMPDACEDEPCDEIREGEEEDNGDESTSN  1400
1401  IPRGLPKPKVAAAQAAAVTNVVAGRVGNLLGKGIGGLSSKLGSGSWF     1447

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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