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

NucPred

Fetching Q09853 from www.uniprot.org...

The NucPred score for your sequence is 0.51 (see score help below)

   1  MSLYDSLLSNLQSINVDTRKKNADLKKLADGSLKFLYTNKNLSQDSLVSK    50
  51  LKGNEAFYKPFLFCCAKKIERHIYISLNSIQLLAINDALSPDILESLFNS   100
 101  LNAVIQLGQDSQLRVLQIIPIICTHYAASMKLPILISLFRICFNLHNSKN   150
 151  SVVSNAAAATLRQIVILVFDYLDYDTLAHKQEADLFLDSLSLFKGLCSLL   200
 201  SAGKSESLNVDHISTTFGLELLESILVNHHRLFQIPEFQDSVRKDLLPII   250
 251  TASLASMSDFPVALRISRILNIIFQHYVTSLTLDIEVIFSFIISSLDNSE   300
 301  AAWKKALFLEVLRSIFSNTNLLYLMYTLFDGNEGRKPIIKKLVTSLSRIV   350
 351  NEKPSVIGVGSRVVLADTFEDYSSTSSGNPPSSMEKVSGSFTGTKPEQII   400
 401  GICRATILKTPCIEQFDKQEPPIIPFAYLVYLAMCSLASISNGIADFVFQ   450
 451  FYEDVGKKEFTLLIEGIKCENFDSKEDSTARPQNIIKCQYGLISENWTSF   500
 501  LVAYSTFVSSALAVELLKFCLNSYVNFVSVCTLFGLETPRDALLTTLSNK   550
 551  AVPSNLLSGNMTHSASSSISHNGRLSTSTMFSVEGLKEAATTIAAIASYD   600
 601  SNHDEKQKCFSLREILFLRCLSSIAKVVGEKMGKGWKILFETFDKADIIL   650
 651  NRSPTSKHLSTSSLNRVNSSNSNFQDSKSFSTLMDYELVSYKNELSELMY   700
 701  VTSSYSQPAYMEFLESLLAVITSSSVHPIQTLTAPRQSFNEDLLSANTKN   750
 751  SVYKTSANRSISGGIRLLRKSSEVFYSFSILETVCSCNLDRFLDSKLDHS   800
 801  GWSLISKSLSEVFKIINVAPELRTRAANCLANILVDVASRLSNENSPDSY   850
 851  AFQEIFFESLGMLLPVTEVSDNTSRGVEYDISTIGLEALVSILETVGHHV   900
 901  LHGWQYVFEMLRFNCLNGATCFGSEKGAKIVRLAFSCLQLICTDFLASLD   950
 951  TSNYLDLMDTLLVFCRQLEDANVSLTAVGLFWNVSDTLKNMFSTSDFSCA  1000
1001  YNSVEDLYAFTSMKSKEILPEVLWIMLLVHLADLCENSWASVRNGAAQIL  1050
1051  FRIFNSQCSKLGTNAWASCCQLVIMKLLHSQPIQNVSDVNNKKDEDDHEQ  1100
1101  TSCLIISGIADVFSENMSLLLNVNGILDVLEEAFQLMLRLHSDIYPKICI  1150
1151  SNFKALRELSFSISEFGKENATFTLLIKLVFINWGRFCEVSFSERRLANI  1200
1201  SQEGLTLLIESVVFLLKAYNFGIEEIKDSLLQVRKAVFYEESTSFALDVD  1250
1251  FLSSLQLAVESLTDLLISKFKLNHLVLELWSDVLTYAFNEEKTIRASLPT  1300
1301  LICLSKKIFENAENVVENHSLDFLNRGTMQHMFESLLVPMRLKYRCPKAS  1350
1351  RVNQSTLPIWVLASKCFVRLMINCFKDLKGSDAIEDAEKMQCLFLLTVEA  1400
1401  TNSIISPNADYEYVWSLEDVFENEDVSSLKQLHNLWKPHLQLNCLSDEVA  1450
1451  QYYITLCKGSFYYQMRNTEDMVISRSNLDIQKEAARNFFPSTESPVSNRR  1500
1501  QRIAVDCFSILLDDYNSSYEHVSLTIRPILQSRLCWSLKRYVADKSVSGY  1550
1551  LPLSKSQEMDMSTVAECLNNHPSLYSNPIHYLLRKAYHTTNASPVATSLN  1600
1601  AILGQLTLKNEVLNAI                                    1616

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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