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

NucPred

Fetching Q06625 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MNRSLLLRLSDTGEPITSCSYGKGVLTLPPIPLPKDAPKDQPLYTVKLLV    50
  51  SAGSPVARDGLVWTNCPPDHNTPFKRDKFYKKIIHSSFHEDDCIDLNVYA   100
 101  PGSYCFYLSFRNDNEKLETTRKYYFVALPMLYINDQFLPLNSIALQSVVS   150
 151  KWLGSDWEPILSKIAAKNYNMVHFTPLQERGESNSPYSIYDQLQFDQEHF   200
 201  KSPEDVKNLVEHIHRDLNMLSLTDIVFNHTANNSPWLVEHPEAGYNHITA   250
 251  PHLISAIELDQELLNFSRNLKSWGYPTELKNIEDLFKIMDGIKVHVLGSL   300
 301  KLWEYYAVNVQTALRDIKAHWNDESNESYSFPENIKDISSDFVKLASFVK   350
 351  DNVTEPNFGTLGERNSNRINVPKFIQLLKLINDGGSDDSESSLATAQNIL   400
 401  NEVNLPLYREYDDDVSEILEQLFNRIKYLRLDDGGPKQGPVTVDVPLTEP   450
 451  YFTRFKGKDGTDYALANNGWIWNGNPLVDFASQNSRAYLRREVIVWGDCV   500
 501  KLRYGKSPEDSPYLWERMSKYIEMNAKIFDGFRIDNCHSTPIHVGEYFLD   550
 551  LARKYNPNLYVVAELFSGSETLDCLFVERLGISSLIREAMQAWSEEELSR   600
 601  LVHKHGGRPIGSYKFVPMDDFSYPADINLNEEHCFNDSNDNSIRCVSEIM   650
 651  IPKILTATPPHALFMDCTHDNETPFEKRTVEDTLPNAALVALCSSAIGSV   700
 701  YGYDEIFPHLLNLVTEKRHYDISTPTGSPSIGITKVKATLNSIRTSIGEK   750
 751  AYDIEDSEMHVHHQGQYITFHRMDVKSGKGWYLIARMKFSDNDDPNETLP   800
 801  PVVLNQSTCSLRFSYALERVGDEIPNDDKFIKGIPTKLKELEGFDISYDD   850
 851  SKKISTIKLPNEFPQGSIAIFETQQNGVDESLDHFIRSGALKATSSLTLE   900
 901  SINSVLYRSEPEEYDVSAGEGGAYIIPNFGKPVYCGLQGWVSVLRKIVFY   950
 951  NDLAHPLSANLRNGHWALDYTISRLNYYSDEAGINEVQNWLRSRFDRVKK  1000
1001  LPSYLVPSYFALIIGILYGCCRLKAIQLMSRNIGKSTLFVQSLSMTSIQM  1050
1051  VSRMKSTSILPGENVPSMAAGLPHFSVNYMRCWGRDVFISLRGMLLTTGR  1100
1101  FDEAKAHILAFAKTLKHGLIPNLLDAGRNPRYNARDAAWFFLQAVQDYVY  1150
1151  IVPDGEKILQEQVTRRFPLDDTYIPVDDPRAFSYSSTLEEIIYEILSRHA  1200
1201  KGIKFREANAGPNLDRVMTDKGFNVEIHVDWSTGLIHGGSQYNCGTWMDK  1250
1251  MGESEKAGSVGIPGTPRDGAAIEINGLLKSALRFVIELKNKGLFKFSDVE  1300
1301  TQDGGRIDFTEWNQLLQDNFEKRYYVPEDPSQDADYDVSAKLGVNRRGIY  1350
1351  RDLYKSGKPYEDYQLRPNFAIAMTVAPELFVPEHAIKAITIADEVLRGPV  1400
1401  GMRTLDPSDYNYRPYYNNGEDSDDFATSKGRNYHQGPEWVWLYGYFLRAF  1450
1451  HHFHFKTSPRCQNAAKEKPSSYLYQQLYYRLKGHRKWIFESVWAGLTELT  1500
1501  NKDGEVCNDSSPTQAWSSACLLDLFYDLWDAYEDDS                1536

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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