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

NucPred

Fetching Q99NE5 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSSAVGPRGPRPPTVPPPMQELPDLSHLTEEERNIIMAVMDRQKEEEEKE    50
  51  EAMLKCVVRDMAKPAACKTPRNAESQPHQPPLNIFRCVCVPRKPSSEEGG   100
 101  PDRNWRLHQQFESYKEQVRKIGEEARRYQGEHKDDAPTCGICHKTKFADG   150
 151  CGHLCSYCRTKFCARCGGRVSLRSNNEDKVVMWVCNLCRKQQEILTKSGA   200
 201  WFFGSGPQQPSQDGTLSDTATGAGSEVPREKKARLQERSRSQTPLSTAAV   250
 251  SSQDTASHGAPLDRNKGAEPSQQALGPEQKQASRSRSEPPRERKKAPGLS   300
 301  EQNGKGGQKSERKRVPKSVVQPGEGTADERERKERRETRRLEKGRSQDYP   350
 351  DRLEKREDGRVAEDEKQRKEEEGVSTPEYTSCEDVELESESVSEKGDLDY   400
 401  WLDPATWHSRETSPISSHPVTWQPSKEGDRLIGRVILNKRTTMPKESGAL   450
 451  LGLKVVGGKMTDLGRLGAFITKVKKGSLADVVGHLRAGDEVLEWNGKPLP   500
 501  GATNEEVYNIILESKSEPQVEIIVSRPIGDIPRIPESSHPPLESSSSSFE   550
 551  SQKMERPSISVISPTSPGALKDAPQVLPGQLSVKLWYDKVGHQLIVNVLQ   600
 601  ATDLPPRVDGRPRNPYVKMYFLPDRSDKSKRRTKTVKKLLEPKWNQTFVY   650
 651  SHVHRRDFRERMLEITVWDQPRVQDEESEFLGEILIELETALLDDEPHWY   700
 701  KLQTHDESSLPLPQPSPFMPRRHIHGESSSKKLQRSQRISDSDISDYEVD   750
 751  DGIGVVPPVGYRASARESKATTLTVPEQQRTTHHRSRSVSPHRGDDQGRP   800
 801  RSRLPNVPLQRSLDEIHPTRRSRSPTRHHDASRSLADHRSRHAESQYSSE   850
 851  PDSELLMLPRAKRGRSAECLHMTSELQPSLDRARSASTNCLRPDTSLHSP   900
 901  ERERGRWSPSLARRRPASPRIQIQHASPENDRHSRKSERSSIQKQSRKGT   950
 951  ASDADRVLPPCLSRRGYAIPRATDQPVIRGKHTTRSRSSEHSSIRTLCSM  1000
1001  HHLAPGGSAPPSPLLTRTHRQGSPTQSPPADTSFGSRRGRQLPQVPVRSG  1050
1051  SIEQASLVVEERTRQMKMKVHRFKQTTGSGSSQELDHEQYSKYNIHKDQY  1100
1101  RSCDNASAKSSDSDVSDVSAISRASSTSRLSSTSFMSEQSERPRGRISSF  1150
1151  TPKMQGRRMGTSGRAIIKSTSVSGEIYTLEHNDGSQSDTAVGTVGAGGKK  1200
1201  RRSSLSAKVVAIVSRRSRSTSQLSQTESGHKKLKSTIQRSTETGMAAEMR  1250
1251  KMVRQPSRESTDGSINSYSSEGNLIFPGVRVGPDSQFSDFLDGLGPAQLV  1300
1301  GRQTLATPAMGDIQIGMEDKKGQLEVEVIRARSLTQKPGSKSTPAPYVKV  1350
1351  YLLENGACIAKKKTRIARKTLDPLYQQSLVFDESPQGKVLQVIVWGDYGR  1400
1401  MDHKCFMGVAQILLEELDLSSMVIGWYKLFPPSSLVDPTLTPLTRRASQS  1450
1451  SLESSSGPPCIRS                                       1463

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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