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

NucPred

Fetching Q92859 from www.uniprot.org...

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

   1  MAAERGARRLLSTPSFWLYCLLLLGRRAPGAAAARSGSAPQSPGASIRTF    50
  51  TPFYFLVEPVDTLSVRGSSVILNCSAYSEPSPKIEWKKDGTFLNLVSDDR   100
 101  RQLLPDGSLFISNVVHSKHNKPDEGYYQCVATVESLGTIISRTAKLIVAG   150
 151  LPRFTSQPEPSSVYAGNNAILNCEVNADLVPFVRWEQNRQPLLLDDRVIK   200
 201  LPSGMLVISNATEGDGGLYRCVVESGGPPKYSDEVELKVLPDPEVISDLV   250
 251  FLKQPSPLVRVIGQDVVLPCVASGLPTPTIKWMKNEEALDTESSERLVLL   300
 301  AGGSLEISDVTEDDAGTYFCIADNGNETIEAQAELTVQAQPEFLKQPTNI   350
 351  YAHESMDIVFECEVTGKPTPTVKWVKNGDMVIPSDYFKIVKEHNLQVLGL   400
 401  VKSDEGFYQCIAENDVGNAQAGAQLIILEHAPATTGPLPSAPRDVVASLV   450
 451  STRFIKLTWRTPASDPHGDNLTYSVFYTKEGIARERVENTSHPGEMQVTI   500
 501  QNLMPATVYIFRVMAQNKHGSGESSAPLRVETQPEVQLPGPAPNLRAYAA   550
 551  SPTSITVTWETPVSGNGEIQNYKLYYMEKGTDKEQDVDVSSHSYTINGLK   600
 601  KYTEYSFRVVAYNKHGPGVSTPDVAVRTLSDVPSAAPQNLSLEVRNSKSI   650
 651  MIHWQPPAPATQNGQITGYKIRYRKASRKSDVTETLVSGTQLSQLIEGLD   700
 701  RGTEYNFRVAALTINGTGPATDWLSAETFESDLDETRVPEVPSSLHVRPL   750
 751  VTSIVVSWTPPENQNIVVRGYAIGYGIGSPHAQTIKVDYKQRYYTIENLD   800
 801  PSSHYVITLKAFNNVGEGIPLYESAVTRPHTDTSEVDLFVINAPYTPVPD   850
 851  PTPMMPPVGVQASILSHDTIRITWADNSLPKHQKITDSRYYTVRWKTNIP   900
 901  ANTKYKNANATTLSYLVTGLKPNTLYEFSVMVTKGRRSSTWSMTAHGTTF   950
 951  ELVPTSPPKDVTVVSKEGKPKTIIVNWQPPSEANGKITGYIIYYSTDVNA  1000
1001  EIHDWVIEPVVGNRLTHQIQELTLDTPYYFKIQARNSKGMGPMSEAVQFR  1050
1051  TPKADSSDKMPNDQASGSGGKGSRLPDLGSDYKPPMSGSNSPHGSPTSPL  1100
1101  DSNMLLVIIVSVGVITIVVVVIIAVFCTRRTTSHQKKKRAACKSVNGSHK  1150
1151  YKGNSKDVKPPDLWIHHERLELKPIDKSPDPNPIMTDTPIPRNSQDITPV  1200
1201  DNSMDSNIHQRRNSYRGHESEDSMSTLAGRRGMRPKMMMPFDSQPPQPVI  1250
1251  SAHPIHSLDNPHHHFHSSSLASPARSHLYHPGSPWPIGTSMSLSDRANST  1300
1301  ESVRNTPSTDTMPASSSQTCCTDHQDPEGATSSSYLASSQEEDSGQSLPT  1350
1351  AHVRPSHPLKSFAVPAIPPPGPPTYDPALPSTPLLSQQALNHHIHSVKTA  1400
1401  SIGTLGRSRPPMPVVVPSAPEVQETTRMLEDSESSYEPDELTKEMAHLEG  1450
1451  LMKDLNAITTA                                         1461

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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