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

NucPred

Fetching Q9VGI8 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MSKKPVAQRKQLTLSSFIGLDGNSQSQPKSRAASVRSKPPAVYNPIFLDA    50
  51  SSSDDETTEISSQSNNGTIATKKSSRDPRTAKLKKHTYLDLSVSPLAKLS   100
 101  AKKYARDSPKKPTSLDLSVSPLAELLAKKSDRDSPKKPVQNENSYTYRGL   150
 151  SESPVENKSIGDTLRKPPQKERKTSIVWLSDSPEKKVTQNERKILDSPLQ   200
 201  RFSFEDFPNKENGNRHHLLTLPDSPPPPQPVKKPEKTMWQNETKTIQDKD   250
 251  SPANPLVSNNLASISTLLDSSRAPNTYKGSSRNLFEDSPEKSGSGEQGYK   300
 301  LGSAKENEIPTKPATASLERNSVTSSPSPAAPLKPRYSVAFDNSLADYLK   350
 351  DLAQNDNFSIDPNKQNTETLKSTLGFFRNTYVELMEKYCSLIDQIPAMHF   400
 401  NEIAGFQPNTFLKLKVMRQKFKARTQLVQNSLDKKESQLKAEQEALEKEE   450
 451  IEMQAEQAQQTVLSSSSPEKSRPIMPLPKVQEIKDEKIPNRNQLIHDLCG   500
 501  EPDNFSPPSSPRDTQLIPKRQQLINDLCGEPDDFSPPSKQNDPHLLRKCE   550
 551  ELVHDLCEEPDDYLAQSMMLDGDLEEEQLNGPTQGTTTSGMDDDEDDLEG   600
 601  LLAEIEDEHQKMQGRRSEFNGYSYKELEAVKVKEKHKETPINISLDDDGF   650
 651  PEYDEAMFEQMHSQAAANKSRVSSAGPSTSKSVVPTKQTSALHSQKLSGN   700
 701  FHANVHNDGITGEFDGQKFEHSTRLMHGLSYSFGLKSFRPNQLQVINATL   750
 751  LGNDCFVLMPTGGGKSLCYQLPAILTEGVTIVISPLKSLIFDQINKLASL   800
 801  DICAKSLSGEQKMADVMAIYRDLESQPPMVKLLYVTPEKISSSARFQDTL   850
 851  DTLNSNNYISRFVIDEAHCVSQWGHDFRPDYKKLGVLKKRFPNVPTIALT   900
 901  ATATPRVRLDILAQLNLKNCKWFLSSFNRSNLRYRVLPKKGVSTLDDISR   950
 951  YIRSKPQHFSGIIYCLSRKECDETSKKMCKDGVRAVSYHAGLTDTDRESR  1000
1001  QKDWLTGKMRVICATVAFGMGIDKPDVRFVLHYSLPKSIEGYYQEAGRAG  1050
1051  RDGDVADCILYYNYSDMLRIKKMLDSDKALQYNVKKIHVDNLYRIVGYCE  1100
1101  NLTDCRRAQQLDYFGEHFTSEQCLENRETACDNCINKRAYKAVDALEHAR  1150
1151  KAARAVKDLCSGRSRFTLLHIADVLKGSKIKKIIDFNHHKTPHHGVLKDW  1200
1201  DKNDVHRLLRKMVIDGFLREDLIFTNDFPQAYLYLGNNISKLMEGTPNFE  1250
1251  FAVTKNAKEAKAAVGSVSDGATSSTADGQSGMREIHERCYTDLLDLCRTI  1300
1301  ASQRNVTMASIMNIQALKSMAETLPITEKDMCSIPHVTKANFDKYGAKLL  1350
1351  EITSNYASEKLLMQAVLDEEEEQAAAKQRPSTSGWNNESVDWDMAVASQG  1400
1401  NANTSGASGFNSFRAGKRKKIYKSGASKRYKTSTTSPAARKTTSARGRGG  1450
1451  RAGAKRAESSASSASGWKSKKTGNSFGFDLMPLPGSK               1487

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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