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

NucPred

Fetching Q92337 from www.uniprot.org...

The NucPred score for your sequence is 0.37 (see score help below)

   1  MKMFQSFFSNYIDINFFRNATLDQCLLLFYLSLFSLTNLFLIQKLFHANH    50
  51  TQHPLKKYFGETCLLEYIQIILSIVSAALSFYLDTNAVWWAIRTITHLEI   100
 101  VGLNILSSLKYGSTLFSWISVANAFGLLLLRLISIYDFLTYSSWSFSVKG   150
 151  GSFLLLLPLAYNITLFLLVIIPLFFPRAWSPTVKFSKVARPSPEQTCSIF   200
 201  SLIFTYGWLNGIIWKSWKKPITLTDVPALPDTECTQIWYSRFAKNDRKSL   250
 251  MHTILLSLKSTILLMVFLSVLVSSTLFVTPLAIKKLLQYLQNPKSDEGNS   300
 301  PFLWVFVLLIGPYLASVVKELYVHVSRRFMLRIKAAITQMIYKKVLTSKT   350
 351  LFVAVDGSKINLDYVYNLLAKDVDNIGEMREFIGIIARAPLEMGVSMYFL   400
 401  YQLLGWSAYVGLLLAILSSSFPLLVASKISRLTSIANTSSDERIRLTTEL   450
 451  LKSIKITKLFGWERPMLSRIQEKRSFEVNNMYSLTLFDIIFKSGMKIAPF   500
 501  ISMFITFAIYTKIMGHQLTPATAFTSISMFGLLRYQFIWLASVSRQFIQF   550
 551  KVSLKRVDNFVYGNMVNDSSIESSDSFVFENTSLSWSPTPSTALFQLKNL   600
 601  NFTIPRNQFTLVVGSTGSGKSTLAMALLGELHVISGKMTTPSISQRIAYV   650
 651  PQAAWLRNGTIRSNILFGEPYDEERYFQIIKACCLDSDLNSMNDGDLTYI   700
 701  HSNGSSLSGGQKQRVSLARALYSNAEVYIFDDIFSALDVSTSRKIYESCF   750
 751  LSTLLQHKTIILFTHNVSLCLPIAENVIVLKNSTAQLVSPDSIQELVPST   800
 801  FFSSNTKKDNIEEENLEPHSFSFDSTLASSSDNDEQRDFASNSSIVLLGL   850
 851  HYLKYFGSNKYILGSILLVMMSQVSLASIHFWIALWSGNSLFSLKLPSSF   900
 901  SFLWGYAILLFIYFLMDLSRAITFAKGGRTASENIHDILSERVLYSPLHW   950
 951  FEKTAAGRILNRFSKDMYATDNLLWASLEGMLLCVMAILITMLNVTLVMP  1000
1001  IFMVPAAFVSLLVYLHGYAYSKAQKQLTSLQSSRTSPVFTMLGETLGGIT  1050
1051  VIRAFKKEKIFEHENMAFIDDMIQPLYISFAINRWLAIRTDGISGLVGFS  1100
1101  TGLIALLRQNIPPGLVGFSLNSAIGFNISVLVFVRANNEILTYINNFRRL  1150
1151  YEYMLLPSEKNESSCLTKPMNKEWPTLGHVSIKNLTVSYSIGQAAVLEDI  1200
1201  NLEILPKEKIAIVGRTGSGKSTMGLTLLRFTMIMSGAVEVDGIDINSLDL  1250
1251  EVLRQRISLIPQDPVLISGTVRSNLDPFEEYGDGELNEILKTASCESLVQ  1300
1301  ASNKNSLDAFAIHLDTPVDSGGVNFSSGQRQILALARALVRKSRIVILDE  1350
1351  STASVDDTTDRRIQQMLRAAFKHATVLCIAHRIKTIVDYDKVLVLDSGKT  1400
1401  VEFGSPKSLYTQRRAFWKMCKESHISL                         1427

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.