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

NucPred

Fetching Q08409 from www.uniprot.org...

The NucPred score for your sequence is 0.39 (see score help below)

   1  MSISKYFTPVADGSLTFNGANIQFGADAQGESKKSYDAEDSMPNPANQLN    50
  51  DITFQAEAGEMVLVLGYPTSTLFKTLFHGKTSLSYSPPGSIKFKNNEFKS   100
 101  FSEKCPHQIIYNNEQDVHFPFLTVEQTIDFALSCKFDIPKGERDQIRNEL   150
 151  LREFGLSHVLKTIVGNDFFRGVSGGERKRISIIETFIANGSVYLWDNSTK   200
 201  GLDSATALDFLEILRKMAKATRSVNLVRISQASDKIVDKFDKILMLSDSY   250
 251  QLFYGTVDECLTYFRDTLGIEKDPNDCIIEYLTSILNFQFKNKNLGNLSN   300
 301  SSSASVLKTATGEVTKYTYNSDFDLYDQWKHSSYYRNIKQQIQGSSIDDS   350
 351  IKEVDPSDVSPIFNIPLKKQLLFCTKRAFQRSLGDKAYMTAQFISVVIQS   400
 401  LVIGSLFYEIPLTTIGSYSRGSLTFFSILFFTFLSLADMPIAFQRQPVVK   450
 451  KQSQLHFYTNWVETLSTTVFDYCFKLCLVIVFSIILYFLAHLQYKAARFF   500
 501  IFLLFLSFYNFCMVSLFALTTLVAPTISVANLFAGILLLAIAMYASYVIY   550
 551  LKNMHPWFVWIAYLNPAMYAMEAILSNELYNLKLDCSETIVPRGPTYNDV   600
 601  PFSHKACAWQGATLGNDYVRGRDYLKQGLSYTYHHVWRNFGIIIGFLVFF   650
 651  IACTLFASQYIKPYFNKDEIERNNSRLTRWLPFLNKKRGTRSSARNDSKY   700
 701  VGIPKSHSVSSSSSSLSAVPYQISPSNKEMALNDYNEQPITETVETQKHI   750
 751  ISWKNINYTVGTKKLINNASGFISSGLTALMGESGAGKTTLLNVLSQRVE   800
 801  TGVVSGEILIDGHPLTDEDAFKRSIGFVQQQDLHLDLLSVKESLEISCLL   850
 851  RGDGDRAYLDTVSNLLKLPSDILVADLNPTQRKLLSIGVELVTKPSLLLF   900
 901  LDEPTSGLDAEAALTIVKFLKQLSLQGQAIFCTIHQPSKSVISHFDNIFL   950
 951  LKRGGECVFFGPMDDACGYFMSHDNTLVYDKEHDNPADFVIDAVGNSNSS  1000
1001  AGKDTAEEALTLNKEAIDWSALWESSVEKKLVKKETARLEDDARASGVDY  1050
1051  TTSLWKQPSYLQQLALITRRQYICTKRDMTYVMAKYCLNGGAGLFIGFSF  1100
1101  WHIKHNIIGLQDSIFFCFMALCVSSPLINQIQDKALKTKEVYVAREARSN  1150
1151  TYHWTVLLLSQSIIELPLALTSSTLFFVCAFFSCGFNNAGWSAGVFFLNY  1200
1201  MLFAAYYSTLGLWLIYTAPNLQTAAVFVAFIYSFTASFCGVMQPYSLFPT  1250
1251  FWKFMYRVSPYTYFVETFVSILLHNWEIKCDMSEMVPGQPLTGQSCGQFM  1300
1301  EAFIEEYGGYLHNKNTFTVCAYCTYTVGDDFLKNENMSYDHVWRNFGIEW  1350
1351  AFVGFNFFAMFAGYYLTYVARIWPKVFKIITKVIPHRGKKPVQN        1394

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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