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

NucPred

Fetching O14066 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MDAIHPVSLRNSKRHPLLHSERNLSRRAVSPSISRSFFQHSNGSFPLFQN    50
  51  HRKSLPSAIYKSVDPYVDANPLDPLAAAKASFADFPEQDDSQSSTSPLSS   100
 101  KYHTKKNKQIFVEDSRRGGAASNAAAIAAKKSGYYERTSTRKRSLTVPTP   150
 151  RTSFPHHPRSRRFSLKNAAIATSYHKFKPLSSNSLSSSGMHFSASKQAFN   200
 201  SPLLQTFSPSPSVSPFSNPAVEKLKTSASKQAAEAQSLREFDFFTPTPEP   250
 251  SDKNLEKLKNGASKQASESQSLKNMESLSLARSSPILTSEKLKNGASKQA   300
 301  IESPPFRASEPLPSSNIIPNPAMERLKNGASKLAIESQPFKSAEPLSSAI   350
 351  PLPNPMSEKMRNGASKQAIMAQSSKINPLPPLTASISDPSFEKLKNTASK   400
 401  QAIESQSLMNSGPELLEPSISDPMLEKMKTDAGKQTVESLSLKSSDATIP   450
 451  KPSVSDLGVEKLKNDASKCAVESQSLMINDPSVSSTSFYNPNMEKLKNGA   500
 501  IKQAIEHQALNAAILNKTQLPYFHQSSSELPISASKRAALSQQTESASKS   550
 551  SSNISEMCDSHPPSNFSISASQQASKDRFSEATSSIDLDLSPGRSLSLAS   600
 601  SKLSVKEAGARVYNRSVATPVMTPSNPFEISKSASQLASIAQVPVSEPAK   650
 651  TSEVNLKKSLSLASSKLSFQEAGTSLKEKTANVQHSPEVLNDRSLASLSA   700
 701  SRHADAISSKSKQHTEIAQPAFNTTGTVLMKTKSNLSDSALSTPQHSDSV   750
 751  LFDITSKAARLASTCAKTDLHRKPRRKHKSFTLENYFGHNAEDESPQSDE   800
 801  VESQTPPSGYSENDIGGTDIYPFALQGAALAAAKDFSRREASLSDSQSAA   850
 851  SMDMLPMKKKLSHSSASSTRSIKSLLTNANQKHIHSSINETDDIPTMAAH   900
 901  IVATGQKNKEKAPSFSNDQALDHLLGSAHKRIPSNKTEWSSSSLHIPSHN   950
 951  SFSDIHHRKIAAHAAAITAASEKLTPSIEETSYSSSKAHDASLSAATLVA  1000
1001  NKDKLIHAPTPQVLAPVLPKVSLPHRHSVSLGQIRGESEVEGDVFYDAPS  1050
1051  DKEDLGSSNAPLDVPHGANRSSMDEVNGSKYDYSDGILDGSGQYTDSDMS  1100
1101  DDENSLKDSQSSVLSFSAVPTKVLKFKLRDVLGSEYSPSPQLLASSSDVS  1150
1151  GSSSAVRAAMKADKIFPAVHENPPPLKTKQSIAKPSPHTLRVPQKKHKHF  1200
1201  YHRDDGKYKSGTNLRKSETVDLPQFFIDENRRKLYEGLWAANKGYLLSKS  1250
1251  EYSKPNDLICNIVVRELWSRSGAPTSVLAKIYDLVDRHHTGVLGRDEFIV  1300
1301  GMFLIDQYLKGRKLPLKVPDSVWLSSKRMGDMLWRLEKLQKKTDNKKPFF  1350
1351  KKKKKKRKHLKKFFDFNTTAKVNEGAMTD                       1379

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.