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

NucPred

Fetching Q07113 from www.uniprot.org...

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

   1  MRAVQLGPVPSGPRVALLPPLLLLLLLAAAGSAQAQAVDLDALCSYTWEA    50
  51  VDSKNNAVYKINVCGNVGISSCGPTSAICMCDLKTENCRSVGDSLLRSSA   100
 101  RSLLEFNTTMGCQPSDSQHRIQTSITFLCGKTLGTPEFVTATDCVHYFEW   150
 151  RTTAACKKDIFKADKEVPCYAFDDKLQKHDLNPLIKLNGGYLVDDSDPDT   200
 201  SLFINVCRDIDSLRDPSTQLRVCPAGTAACLLKGNQAFDVGRPKEGLKLL   250
 251  SKDRLVLTYVKEEGEKPDFCNGHSPAVTVTFVCPSERREGTIPKLTAKSN   300
 301  CRYEVEWITEYACHRDYLQSESCSLSSEQHDITIDLSPLAQYGGSPYVSD   350
 351  GREYTFFINVCGDTKVSLCNNKEAAVCQEKKADSTQVKIAGRHQNQTLRY   400
 401  SDGDLTLIYSGGDECSSGFQRMSVINFECNKTAGKDGRGEPVFTGEVDCT   450
 451  YFFTWDTKYACIKEKEDLLCGAINGKKRYDLSVLARHSESEQNWEAVDGS   500
 501  QAESEKYFFINVCHRVLQEGKARNCPEDAAVCAVDKNGSKNLGKFVSSPT   550
 551  KEKGHIQLSYTDGDDCGSDKKISTNITLVCKPGDLESAPVLRAARSDGCF   600
 601  YEFEWHTAAACVLSKTEGENCTVLDAQAGFSFDLSLLTKKNGAYKVETEK   650
 651  YDFYINVCGPVSMDPCQSNSGACQVAKSGKSWNLGLSSTKLTYYDGMIQL   700
 701  SYRNGTPYNNEKHTPRATLITFLCDRDAGVGFPEYQEEDNSTYNFRWYTS   750
 751  YACPEEPLECMVTDPSMMEQYDLSSLVKSEGGSGGNWYAMENSREHVTRR   800
 801  KYYLNVCRPLNPVPGCDRYASACQMKYENHEGSLAETVSISNLGVAKIGP   850
 851  VVEESGSLLLEYVNGSACTTSDGQLTTYSTRIHLVCGRGFMNSHPIFTFN   900
 901  WECVVSFLWNTEAACPIQTITETDQACSIRDPSSGFVFNLSPLNDSAQGH   950
 951  VVLGIGKTFVFNICGAMPACGTVAGKPAYGCEAETQIEDIKDLRPQRPVG  1000
1001  MERSLQLSAEGFLTLTYKGSSPSDRGTAFIIRFICNDDIYPGAPKFLHQD  1050
1051  IDSTRGIRNTYFEFETALACTPSLVDCQVTDPAGNEYDLSALSMVRKPWT  1100
1101  AVDTSAYGKRRHFYLSVCNPLPYIPGCHGIALGSCMVSEDNSFNLGVVQI  1150
1151  SPQATGNGSLSILYVNGDRCGDQRFSTRIVFECAQTSGSPMFQFVNNCEY  1200
1201  VFVWRTVEACPVIREEGDNCQVKDPRHGNLYDLKPLGLNDTIVSVGEYTY  1250
1251  YLRVCGKLSSDVCSAHDGSKAVSSCQEKKGPQGFQKVAGLLSQKLTFENG  1300
1301  LLKMNYTGGDTCHKVYQRSTTIYFYCDRTTQKPVFLKETSDCSYMFEWRT  1350
1351  QYACPPFNVTECSVQDAAGNSIDLSSLSRYSDNWEAVTRTGATEHYLINV  1400
1401  CKSLSPHAGTEPCPPEAAVCLLNGSKPVNLGKVRDGPQWTDGVTVLQYVD  1450
1451  GDLCPDKIRRRSTIIRFTCSDNQVNSRPLFISAVQDCEYTFSWPTPSACP  1500
1501  VKSNTHDDCQVTNPSTGHLFDLSSLSGRAGINASYSEKGLVFMSICEENE  1550
1551  NCGPGVGACFGQTRISVGKASKRLSYKDQVLQLVYENGSPCPSLSDLRYK  1600
1601  SVISFVCRPEAGPTNRPMLISLDKQTCTLFFSWHTPLACEQATECTVRNG  1650
1651  SSIIDLSPLIHRTGGYEAYDESEDDTSDTTPDFYINICQPLNPMHGVPCP  1700
1701  AGASVCKVPVDGPPIDIGRVTGPPIFNPVANEVYLNFESSTHCLADRYMN  1750
1751  YTSLITFHCKRGVSMGTPKLIRTNDCDFVFEWETPIVCPDEVKTQGCAVT  1800
1801  DEQLLYSFNLTSLSTSTFKVTRDARTYSIGVCTAAAGLGQEGCKDGGVCL  1850
1851  LSGNKGASFGRLASMQLDYRHQDEAVILSYVNGDPCPPETDDGEPCVFPF  1900
1901  IYKGKSYDECVLEGRAKLWCSKTANYDRDHEWGFCRQTNSYRMSAIIFTC  1950
1951  DESEDIGRPQVFSEDRGCEVTFEWKTKVVCPPKKMECKFVQKHKTYDLRL  2000
2001  LSSLTGSWDFVHEGNSYFINLCQRVYKGPLDCSERASICKKSATGQVQVL  2050
2051  GLVHTQKLEVIDETVIVTYSKGYPCGGNKTASSVIELTCAKTVGRPAFKR  2100
2101  FDSVSCTYYFYWYSRAACAVRPQEVTMVNGTLTNPVTGKSFSLGEIYFKL  2150
2151  FSASGDMRTNGDNYLYEIQLSSITSSSYPACAGANICQVKPNDQHFSRKV  2200
2201  GTSDMTKYYVQDGDLDVVFTSSSKCGKDKTKSVSSTIFFHCDPLVKDGIP  2250
2251  EFSHETADCQYLFSWYTSAVCPLGVDFEDESAGPEYKGLSERSQAVGAVL  2300
2301  SLLLVALTGCLLALLLHKKERRETVINKLTSCCRRSSGVSYKYSKVSKEE  2350
2351  ETDENETEWLMEEIQVPAPRLGKDGQENGHITTKAVKAEALSSLHGDDQD  2400
2401  SEDEVLTVPEVKVHSGRGAEVESSQPLRNPQRKVLKEREGERLGLVRGEK  2450
2451  ARKGKFRPGQRKPTAPAKLVSFHDDSDEDLLHI                   2483

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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