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

NucPred

Fetching P40064 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MYSTPLKKRIDYDRETFTASASLGGNRLRNRPRDDQNNGKPNLSSRSFLS    50
  51  ERKTRKDVLNKYGEAGNTIESELRDVTTHVKISGLTSSEPLQLASEFVQD   100
 101  LSFRDRNTPILDNPDYYSKGLDYNFSDEVGGLGAFTPFQRQQVTNIPDEV   150
 151  LSQVSNTEIKSDMGIFLELNYCWITSDNKLILWNINNSSEYHCIDEIEHT   200
 201  ILKVKLVKPSPNTFVSSVENLLIVATLFDIYILTISFNDRTHELNIFNTG   250
 251  LKVNVTGFNVSNIISYERTGQIFFTGATDGVNVWELQYNCSENLFNSKSN   300
 301  KICLTKSNLANLLPTKLIPSIPGGKLIQKVLEGDAGTEEETISQLEVDQS   350
 351  RGVLHTLSTKSIVRSYLITSNGLVGPVLIDAAHIRRGMNALGVKNSPLLS   400
 401  NRAFKIAKIVSISMCENNDLFLAVITTTGVRLYFKGSISRRSIGSLKLDS   450
 451  VKFPPTSISSSLEQNKSFIIGHHPLNTHDTGPLSTQKASSTYINTTCAST   500
 501  IISPGIYFTCVRKRANSGELSKGITNKALLENKEEHKLYVSAPDYGILKN   550
 551  YGKYVENTALLDTTDEIKEIVPLTRSFNYTSTPQGYANVFASQYSAEPLK   600
 601  VAVLTSNALEIYCYRTPDEVFESLIENPLPFIHSYGLSEACSTALYLACK   650
 651  FNKSEHIKSSALAFFSAGIPGVVEIKPKSSRESGSVPPISQNLFDKSGEC   700
 701  DGIVLSPRFYGSALLITRLFSQIWEERVFVFKRASKTEKMDAFGISITRP   750
 751  QVEYYLSSISVLADFFNIHRPSFVSFVPPKGSNAITASDAESIAMNALIL   800
 801  LINSIKDALSLINVFYEDIDAFKSLLNTLMGAGGVYDSKTREYFFDLKFH   850
 851  DLFTPNAKTKQLIKEILIEVVNANIASGTSADYIVNVLKERFGSFCHSAD   900
 901  ILCYRAGEHLEAAQKFEMIDSKISRNHLDTAIDLYERCAENIELCELRRV   950
 951  VDIMVKLNYQPKTVGFLLRFADKIDKGNQAQEYVSRGCNTADPRKVFYDK  1000
1001  RINVYTLIFEIVKSVDDYTSIEQSPSIANISIFSPASSLKKRVYSVIMNS  1050
1051  NNRFFHYCFYDWLVANKRQDYLLRLDSQFVLPYLKERAEKSLEISNLLWF  1100
1101  YLFKEEHFLEAADVLYALASSDFDLKLSERIECLARANGLCDSSTSFDQK  1150
1151  PALVQLSENIHELFDIASIQDDLLNLVRNETRIDEDYRKQLTLKLNGRVL  1200
1201  PLSDLFNDCADPLDYYEIKLRIFKVSQFKDEKVIQGEWNRLLDSMKNAPS  1250
1251  PDVGSVGQESFLSSISNTLIRIGKTTRDTDVVFPVHFLMNKILESFIDKS  1300
1301  SAADGSVCSMFLLAGVSHLKLYYILSRIIENSEGNVELAKKEMVWLIKDW  1350
1351  YQSDSDLRGSIAPEQIKKLEKYDPNTDPVQDYVKDRHHGLK           1391

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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