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

NucPred

Fetching O61363 from www.uniprot.org...

The NucPred score for your sequence is 0.35 (see score help below)

   1  NLIRKDVDALSEDEVLNLQVALRAMQDDETPTGYQAIAAYHGEPADCKAP    50
  51  DGSTVVCCLHGMPTFPLWHRLYTVQFEQTMVAHGSKLGVPYWDWTQPLNH   100
 101  LPELVSHPLFMDPTAHKAKKNVFYSGDIAFEKKTTARAVDTRLFQASKGG   150
 151  KNFLLEGVLSALEQDDYCHFEVQFEVAHNPIHYLVGGRFTHSMSSLEYTS   200
 201  YDPLFFLHHSNVERLFTIWQALQKHRGLDGNANCGLNMFHKPMEPFGRDT   250
 251  NPISLTKEHAKAVDVFNYNELGYDYDDLHLNGMDIPELDTMLKERQQHPR   300
 301  SFANFRLGGIKTSANVRVAVCIPSEDKRHSDNCNNHVGSFFILGGVHEMT   350
 351  WDFGYPFLFEITDVVKSLGIPLDGNYYVHADVTEINGTLLPDGTIPRPTV   400
 401  SYIPHNFKDADMVVVDKTGLNVRKDLQSLTTEEEYELRVAMERFMDDKSI   450
 451  DGYQALAEFHGLPAKCPEPDAINRVACCVHGMSTFPHWHRLVVMQFEDAL   500
 501  LARGSPIGVPYWDWTTPSSSLPHLVAVETYEDPYTKEVKPNPFYHAQIEF   550
 551  LHNDVFTARNVDSRLFEKPTKGHHGYLHDGMLLAFEQEDFCDFEVQFEVT   600
 601  HNAIHAWVGGNEPYSMSSLHYTSFDPLFWLHHSQVDRLWAVWQALQIYRG   650
 651  KPYKPYCALSEVHRPLKPFAFEPPLNNNKHTHSHSVPTHVYDYQSDLHYT   700
 701  YDTLFFGGMSVRELQRHIEEDKAKDRVFVGFLLMGIKTSANVVINVESAG   750
 751  NTYMAGTITILGGSKEMEWRFDRLYKYEITDALAELGVDMHAEYSINLQI   800
 801  NDINGTALPPTSIPDPIVIFSPGKKESGVVFDELYRSRRDVSSLTDADMN   850
 851  ALRKALQAYEDDKDASGYQQVAAFHGSTKWCPSPDAEVKYACCHHGMATF   900
 901  PHWHRLLTVNFENGLRHNGYQNGIPYWDWTRPLSELPTLVKDETYADENG   950
 951  ETHPNPFFSGVIDEIGEHTTRSPNPTLFLKPPFGHFTPLGDEVMYALEQE  1000
1001  DFCSFEVQFEIAHNHIHALVGGTEPYSMSSLEYTTFDPIFILHHSNVDRI  1050
1051  WAIWQALQKFRGHRYNSANCAIETLRKPMSPFSLTSDINIDPMTREHSVP  1100
1101  FDVFDYKKNFHYEYDLLELNGLSIPQLHREISRRRAKSRIFATFMLEGIK  1150
1151  QSALVEYYIRAHGSTDQLKAGEFYILGSANEMPWKFDRVYKADITQQMKE  1200
1201  ANLHFNDQYHIEYHLKDLSGNEIAGVHLETAIIYEPGLGNFGEAGIWVEP  1250
1251  VTSANRIRKNLNALTDGDMESLRKAFKDMTTDGRYEEIASFHGLPAQCPN  1300
1301  KDGSKVYTCCIHGMPTFPHWHRLYVALVENELLARGSGVAVPYWDWVQPF  1350
1351  DHLPALVNRATYYNSRTLLVEPNPFFKGKISFLNSETNRDPQEELFGNKY  1400
1401  LYEHTLFVLEQTDFCDFEVHFEVLHNTIHSWLGGRDPHSMSSLDFAAYDP  1450
1451  IFFLHHSNIDRIWAIWQELQRYRKLPYNEANCALPLLNVPMRPFSNTTAN  1500
1501  HDRMTLTHSAPNDVFDYQNVLHYKYDTLSFYDLTITQLDHLIEERKSHDR  1550
1551  IFAGFLLHGVQASADIHVFICVPTSKHEENCAHDVGVFSVLGGKSEMPWQ  1600
1601  FASVFQYEITDQLKLLGLNQNSHFRGVTEVTAVNGSSINSDIFPHPTIIY  1650
1651  VPKQDHSADIKSEEGNEYLVRKNVERLSLSEMNSLIHAFRRMQRDKSSDG  1700
1701  FEAIASFHALPPLCPSPTAKHRHACCLHGMATFPHWHRLYVVQFEQALHR  1750
1751  HGATVGVPYWDWTRPISKIPDFIASKRYSDPFTKIEDYNPFNQGQISFIS  1800
1801  EDTETKREVSEYLFEHPVLGKQTWLFDNIALALEQTDYCDFEIQLEIVHN  1850
1851  AIHSWIGGKEEHSLNHLHYAAYDPIFYLHHSNVDRLWVIWQELQKLRGLN  1900
1901  AYESHCALELMKVPLKPFSFGAPYNLNDLTTKLSKPEDMFRYKDNFHYEY  1950
1951  DILDINSMSINQIESSYIRHQRDHDRVFAGFLLSGFGSSAYATFEICIEG  2000
2001  GECHEGSHFSVLGGSTEMPWAFDRLYKIEITDILSDMNLAFDSAFTIKTK  2050
2051  LVAQNGTELPASILPEATVIRIPPSNEDADIDTPLNHIRRNVESLDERDI  2100
2101  QNLMAALTRVKEDESDHGFQTIASYHGSTLCPSPEEPKYACCLHGMPVFP  2150
2151  HWHRVYLLHFEDSMRRHGSSVATPYWDWTQPGTKLPRLLADSDYYDAWTD  2200
2201  NVTENPFLRGYIKTEDTYTVRDVKPELFEIGGGEGSTLYQQVLLMLEQED  2250
2251  YCDFEVQFEVVHNSIHYLVGGHQKYAMSSLVYSSFDPIFYVHHSMVDRLW  2300
2301  AIWQALQEHRHLPFDKAYCALEQLSFPMKPFVWESNPNLHTRAASTPQHL  2350
2351  FDDNKLGYKYDNLEFHGMNIDQLENAIHKQQNKDRVFASFLLFGIKTSAD  2400
2401  VHLKLCKDETCEDAGVVFILGGDNEMPWHFDRTYKKDITHVLHQMHIPLE  2450
2451  DLYVHGSTILLEVEIETVDGKVLDSSSLPAPSMIYVPAKDFKREVHKKTV  2500
2501  GDAIIRKNVNSLTPSDIKELRDAMAKVQADTSDNGYQKIASYHGIPLSCH  2550
2551  YENGTAYACCQHGMVTFPNWHRLLTKQMEDALVAKGSHVGIPYWDWTTTF  2600
2601  ANLPVLVTEEKDNSFHHAHIDVANTDTTRSPRAQLFDDPDKGDKSFFYRQ  2650
2651  IALALEQTDFCDFEIQFEIGHNAIHSWVGGSSPYGMSTLHYTSYDPLFYL  2700
2701  HHSNTDRIWSVWQALQKYRGLPYNTANCEINKLVKPLKPFNLDTNPNAVT  2750
2751  KAHSTGATSFDYHKLGYDYDNLNFHGMTIPELEEHLKEIQHEDRVFAGFL  2800
2801  LRTIGQSADVNFDVCTKDGECTFGGTFCILGGEHEMFWAFDRPFKYDITT  2850
2851  SLKHLRLDAHDDFDIKVTIKGIDGHVLSNKYLSPPTVFLAPAKTTH      2896

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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