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

NucPred

Fetching Q5JY77 from www.uniprot.org...

The NucPred score for your sequence is 0.57 (see score help below)

   1  MTGAEIESGAQVKPEKKPGEEVVGGAEIENDVPLVVRPKVRTQAQIMPGA    50
  51  RPKNKSKVMPGASTKVETSAVGGARPKSKAKAIPVSRFKEEAQMWAQPRF   100
 101  GAERLSKTERNSQTNIIASPLVSTDSVLVAKTKYLSEDRELVNTDTESFP   150
 151  RRKAHYQAGFQPSFRSKEETNMGSWCCPRPTSKQEASPNSDFKWVDKSVS   200
 201  SLFWSGDEVTAKFHPGNRVKDSNRSMHMANQEANTMSRSQTNQELYIASS   250
 251  SGSEDESVKTPWFWARDKTNTWSGPREDPNSRSRFRSKKEVYVESSSGSE   300
 301  HEDHLESWFGAGKEAKFRSKMRAGKEANNRARHRAKREACIDFMPGSIDV   350
 351  IKKESCFWPEENANTFSRPMIKKEARARAMTKEEAKTKARARAKQEARSE   400
 401  EEALIGTWFWATDESSMADEASIESSLQVEDESIIGSWFWTEEEASMGTG   450
 451  ASSKSRPRTDGERIGDSLFGAREKTSMKTGAEATSESILAADDEQVIIGS   500
 501  WFWAGEEVNQEAEEETIFGSWFWVIDAASVESGVGVSCESRTRSEEEEVI   550
 551  GPWFWSGEQVDIEAGIGEEARPGAEEETIFGSWFWAENQTYMDCRAETSC   600
 601  DTMQGAEEEEPIIGSWFWTRVEACVEGDVNSKSSLEDKEEAMIPCFGAKE   650
 651  EVSMKHGTGVRCRFMAGAEETNNKSCFWAEKEPCMYPAGGGSWKSRPEEE   700
 701  EDIVNSWFWSRKYTKPEAIIGSWLWATEESNIDGTGEKAKLLTEEETIIN   750
 751  SWFWKEDEAISEATDREESRPEAEEGDIIGSWFWAGEEDRLEPAAETREE   800
 801  DRLAAEKEGIVGSWFGAREETIRREAGSCSKSSPKAEEEEVIIGSWFWEE   850
 851  EASPEAVAGVGFESKPGTEEEEITVGSWFWPEEEASIQAGSQAVEEMESE   900
 901  TEEETIFGSWFWDGKEVSEEAGPCCVSKPEDDEEMIVESWFWSRDKAIKE   950
 951  TGTVATCESKPENEEGAIVGSWFEAEDEVDNRTDNGSNCGSRTLADEDEA  1000
1001  IVGSWFWAGDEAHFESNPSPVFRAICRSTCSVEQEPDPSRRPQSWEEVTV  1050
1051  QFKPGPWGRVGFPSISPFRFPKEAASLFCEMFGGKPRNMVLSPEGEDQES  1100
1101  LLQPDQPSPEFPFQYDPSYRSVQEIREHLRAKESTEPESSSCNCIQCELK  1150
1151  IGSEEFEELLLLMEKIRDPFIHEISKIAMGMRSASQFTRDFIRDSGVVSL  1200
1201  IETLLNYPSSRVRTSFLENMIRMAPPYPNLNIIQTYICKVCEETLAYSVD  1250
1251  SPEQLSGIRMIRHLTTTTDYHTLVANYMSGFLSLLATGNAKTRFHVLKML  1300
1301  LNLSENLFMTKELLSAEAVSEFIGLFNREETNDNIQIVLAIFENIGNNIK  1350
1351  KETVFSDDDFNIEPLISAFHKVEKFAKELQGKTDNQNDPEGDQEN       1395

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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