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

NucPred

Fetching P97798 from www.uniprot.org...

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

   1  MAAEREAGRLLCTSSSRRCCPPPPLLLLLPLLLLLGRPASGAAATKSGSP    50
  51  PQSAGASVRTFTPFYFLVEPVDTLSVRGSSVILNCSAYSEPSPNIEWKKD   100
 101  GTFLNLESDDRRQLLPDGSLFISNVVHSKHNKPDEGFYQCVATVDNLGTI   150
 151  VSRTAKLTVAGLPRFTSQPEPSSVYVGNSAILNCEVNADLVPFVRWEQNR   200
 201  QPLLLDDRIVKLPSGTLVISNATEGDGGLYRCIVESGGPPKFSDEAELKV   250
 251  LQDPEEIVDLVFLMRPSSMMKVTGQSAVLPCVVSGLPAPVVRWMKNEEVL   300
 301  DTESSGRLVLLAGGCLEISDVTEDDAGTYFCIADNGNKTVEAQAELTVQV   350
 351  PPGFLKQPANIYAHESMDIVFECEVTGKPTPTVKWVKNGDVVIPSDYFKI   400
 401  VKEHNLQVLGLVKSDEGFYQCIAENDVGNAQAGAQLIILEHDVAIPTLPP   450
 451  TSLTSATTDHLAPATTGPLPSAPRDVVASLVSTRFIKLTWRTPASDPHGD   500
 501  NLTYSVFYTKEGVARERVENTSQPGEMQVTIQNLMPATVYIFKVMAQNKH   550
 551  GSGESSAPLRVETQPEVQLPGPAPNIRAYATSPTSITVTWETPLSGNGEI   600
 601  QNYKLYYMEKGTDKEQDIDVSSHSYTINGLKKYTEYSFRVVAYNKHGPGV   650
 651  STQDVAVRTLSDVPSAAPQNLSLEVRNSKSIVIHWQPPSSTTQNGQITGY   700
 701  KIRYRKASRKSDVTETLVTGTQLSQLIEGLDRGTEYNFRVAALTVNGTGP   750
 751  ATDWLSAETFESDLDETRVPEVPSSLHVRPLVTSIVVSWTPPENQNIVVR   800
 801  GYAIGYGIGSPHAQTIKVDYKQRYYTIENLDPSSHYVITLKAFNNVGEGI   850
 851  PLYESAVTRPHTDTSEVDLFVINAPYTPVPDPTPMMPPVGVQASILSHDT   900
 901  IRITWADNSLPKHQKITDSRYYTVRWKTNIPANTKYKNANATTLSYLVTG   950
 951  LKPNTLYEFSVMVTKGRRSSTWSMTAHGATFELVPTSPPKDVTVVSKEGK  1000
1001  PRTIIVNWQPPSEANGKITGYIIYYSTDVNAEIHDWVIEPVVGNRLTHQI  1050
1051  QELTLDTPYYFKIQARNSKGMGPMSEAVQFRTPKADSSDKMPNDQALGSA  1100
1101  GKGSRLPDLGSDYKPPMSGSNSPHGSPTSPLDSNMLLVIIVSVGVITIVV  1150
1151  VVVIAVFCTRRTTSHQKKKRAACKSVNGSHKYKGNCKDVKPPDLWIHHER  1200
1201  LELKPIDKSPDPNPVMTDTPIPRNSQDITPVDNSMDSNIHQRRNSYRGHE  1250
1251  SEDSMSTLAGRRGMRPKMMMPFDSQPPQPVISAHPIHSLDNPHHHFHSSS  1300
1301  LASPARSHLYHPSSPWPIGTSMSLSDRANSTESVRNTPSTDTMPASSSQT  1350
1351  CCTDHQDPEGATSSSYLASSQEEDSGQSLPTAHVRPSHPLKSFAVPAIPP  1400
1401  PGPPLYDPALPSTPLLSQQALNHHIHSVKTASIGTLGRSRPPMPVVVPSA  1450
1451  PEVQETTRMLEDSESSYEPDELTKEMAHLEGLMKDLNAITTA          1492

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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