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

NucPred

Fetching Q9NG98 from www.uniprot.org...

The NucPred score for your sequence is 0.55 (see score help below)

   1  MKAVLTCFRPVVASHRRYCANPGQAMKYLNVAEKNDAAKTIAGLLSNGAA    50
  51  QRREGYSVYNKVFDFEAPVRGQNAKMVMTSVSGHMMQLAFQVSYKNWRTV   100
 101  DPRSLFDAPVKKGVGSDYEPIKRTLEREVRGCQGLIIWTDCDREGENIGY   150
 151  EIIDVCRAIKPNISVYRATFSEITTVAVRRALQQLGQPDKRQSDAVDVRT   200
 201  ELDLRTGAAITRFQTMRLQRLFPEKIADKLISYGSCQIPTLGFVAERYKE   250
 251  IEAFVSEPFWKIKVLHTIDDLTVEFNWARNRLFDKEACENYLLLCLAEPD   300
 301  PRALVESVTVKPKHKWRPTPLDTVEMEKLGSRKLKLSAKETMTIAEKLYT   350
 351  KGFISYPRTETNQFSKEFALAPLVEMQTGHRDWGAFAQRVIEWGPNPRNG   400
 401  NKSDQAHPPIHPTKLAENLQGNEARVYELVVRHFLACVSKDAVGSETLVH   450
 451  IDIAGEKFTANGLVIHERNYLDVYVYDKWSAKQIHHYENGQRFEPTEVSL   500
 501  HEGATTAPPLLTEADLIALMEKHGIGTDATHAEHINTIKERGYIGVLDKG   550
 551  FLVPGVIGMGLYEGYDAMELALAKPQLRAEFELDLKLICQGQKDPKVVLT   600
 601  EQIAKYKQAYQQITDKITAMDAKISARINETPAANSAVQEGADGSAPSHG   650
 651  IIQSIFQCPKCNEAPLALKPKKNQQGWYIGCNNFPDCKNAVWLPTECKDA   700
 701  SVLDECCPTCGDGYRMLKFRLSTPYYRGVFGTPSGWYKTCLPCDNLFRTT   750
 751  FNINLDSVKKVGGIVGEVRGGGGGPGPGPGGGGSGRGAGSGGWSSGPGGG   800
 801  GSGGGGGSGGWGSGTGGGGSGGWGSGTGGGGLGGGKGKKPGGESKKSATK   850
 851  KPPNEPKPKKTKEPKAAPNKKTSSKSSGSIRSFFTSAAPTNSASNGLDEF   900
 901  FDSNDGFEDAMLAAAESVESSSQPKTISMVPLDDDIAAAFAADDDAEFEA   950
 951  LVNGGTMPTESNGDQQLDKSLSEWIKEQDKADERPMLWGTRERASLGTAA  1000
1001  PTPPPKPAAKRPRWDSVERDSTPPSSVPESETVLCTGCQQPARQNTVRKN  1050
1051  GPNLGRLYYKCPKPDECNFFQWADEPPSSAKSKNSTGSAPQSTTSWGSNR  1100
1101  VVTLPSIQQSNSQRGQSSMRSNSSSTVTITQTKTKQQERNTATPGDGEEV  1150
1151  MCNCGQLASQLTVRKDGPNQGRPFYACPTREKSCGFFKWGDEDQNQGASS  1200
1201  TSWGSANRNPPGRSQPTAITSDGPKTRRCGLCRKEGHTRNKCPRKDEFDM  1250

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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