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

NucPred

Fetching P97603 from www.uniprot.org...

The NucPred score for your sequence is 0.50 (see score help below)

   1  AAAKNGSPPQSAGASVRTFTPLYFLVEPVDTLSVRGSSVILNCSAYSEPS    50
  51  PNIEWKKDGTFLNLVSDDRRQLLPDGSLFISNVVHSKHNKPDEGFYQCVA   100
 101  TVDNLGTIVSRTAKLAVAGLPRFTSQPEPSSIYVGNSGILNCEVNADLVP   150
 151  FVRWEQNRQPLLLDDRIVKLPSGTLVISNATEGDEGLYRCIVESGGPPKF   200
 201  SDEAELKVLQESEEMLDLVFLMRPSSMIKVIGQSAVLPCVASGLPAPVIR   250
 251  WMKNEDVLDTESSGRLALLAGGSLEISDVTEDDAGTYFCVADNGNKTIEA   300
 301  QAELTVQVPPEFLKQPANIYARESMDIVFECEVTGKPAPTVKWVKNGDVV   350
 351  IPSDYFKIVKEHNLQVLGLVKSDEGFYQCIAENDVGNAQAGAQLIILEHA   400
 401  PATTGPLPSAPRDVVASLVSTRFIKLTWRTPASDPHGDNLTYSVFYTKEG   450
 451  VARERVENTSQPGEMQVTIQNLMPATVYIFKVMAQNKHGSGESSAPLRVE   500
 501  TQPEVQLPGPAPNIRAYATSPTSITVTWETPLSGNGEIQNYKLYYMEKGT   550
 551  DKEQDVDVSSHSYTINGLKKYTEYSFRVVAYNKHGPGVSTQDVAVRTLSD   600
 601  VPSAAPQNLSLEVRNSKSIVIHWQPPSSATQNGQITGYKIRYRKASRKSD   650
 651  VTETVVTGTQLSQLIEGLDRGTEYNFRVAALTVNGTGPATDWLSAETFES   700
 701  DLDESRVPEVPSSLHVRPLVTSIVVSWTPPENQNIVVRGYAIGYGIGSPH   750
 751  AQTIKVDYKQRYYTIENLDPSSHYVITLKAFNNVGEGIPLYESAVTRPHT   800
 801  DTSEVDLFVINAPYTPVPDPTPMMPPVGVQASILSHDTIRITWADNSLPK   850
 851  HQKITDSRYYTVRWKTNIPANTKYKNANATTLSYLVTGLKPNTLYEFSVM   900
 901  VTKGRRSSTWSMTAHGATFELVPTSPPKDVTVVSKEGKPRTIIVNWQPPS   950
 951  EANGKITGYIIYYSTDVNAEIHDWVIEPVVGNRLTHQIQELTLDTPYYFK  1000
1001  IQARNSKGMGPMSEAVQFRTPKADSSDKMPNDQALGSAGKGGRLPDLGSD  1050
1051  YKPPMSGSNSPHGSPTSPLDSNMLLVIIVSIGVITIVVVVIIAVFCTRRT  1100
1101  TSHQKKKRAACKSVNGSHKYKGNCKDVKPPDLWIHHERLELKPIDKSPDP  1150
1151  NPVMTDTPIPRNSQDITPVDNSMDSNIHQRRNSYRGHESEDSMSTLAGRR  1200
1201  GMRPKMMMPFDSQPPQQSVRNTPSTDTMPASSSQTCCTDHQDPEGATSSS  1250
1251  YLASSQEEDSGQSLPTAHVRPSHPLKSFAVPAIPPPGPPIYDPALPSTPL  1300
1301  LSQQALNHHLHSVKTASIGTLGRSRPPMPVVVPSAPEVQEATRMLEDSES  1350
1351  SYEPDELTKEMAHLEGLMKDLNAITTA                         1377

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.)

Go back to the NucPred Home Page.