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

NucPred

Fetching Q7TMY8 from www.uniprot.org...

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

   1  MKVDRTKLKKTPTEAPADCRALIDKLKVCNDEQLLLELQQIKTWNIGKCE    50
  51  LYHWVDLLDRFDGILADAGQTVENMSWMLVCDRPEKEQLKMLLLAVLNFT   100
 101  ALLIEYSFSRHLYSSIEHLTTLLASSDMQVVLAVLNLLYVFSKRSNYITR   150
 151  LGSDKRTPLLTRLQHLAESWGGKENGFGLAECCRDLQMLKYPPSATTLHF   200
 201  EFYADPGAEVKIEKRTTSNTLHYIHIEQLDKISESPSEIMESLTKMYSIP   250
 251  KDKQMLLFTHIRLAHGFSNHRKRLQAVQARLHAISILVYSNALQESANSI   300
 301  LYNGLIEELVDVLQITDKQLMEIKAASLRTLTSIVHLERTPKLSSIIDCT   350
 351  GTASYHGFLPVLVRNCIQAMIDPSMDPYPHQFATALFSFLYHLASYDAGG   400
 401  EALVSCGMMEALLKVIKFLGDEQDQITFVTRAVRVVDLITNLDMAAFQSH   450
 451  SGLSIFIYRLEHEVDLCRKECPFVIKPKIQRPSTTQEGEEMETDMDGVQC   500
 501  IPQRAALLKSMLNFLKKAIQDPAFSDGIRHVMDGSLPTSLKHIISNAEYY   550
 551  GPSLFLLATEVVTVFVFQEPSLLSSLQDNGLTDVMLHALLIKDVPATREV   600
 601  LGSLPNVFSALCLNARGLQSFVQCQPFERLFKVLLSPDYLPAMRRRRSSD   650
 651  PLGDTASNLGSAVDELMRHQPTLKTDATTAIIKLLEEICNLGRDPKYICQ   700
 701  KPSIQKADGTATAPPPRSNHAAEEASSEDEEEEEVQAMQSFNSAQQNETE   750
 751  PNQQVVGTEERIPIPLMDYILNVMKFVESILSNNTTDDHCQEFVNQKGLL   800
 801  PLVTILGLPNLPIDFPTSAACQAVAGVCKSILTLSHEPKVLQEGLLQLDL   850
 851  ILSSLEPLHRPIESPGGSVLLRELACAGNVADATLSAQATPLLHALTAAH   900
 901  AYIMMFVHTCRVGQSEIRSISVNQWGSQLGLSVLSKLSQLYCSLVWESTV   950
 951  LLSLCTPNSLPSGCEFGQADMQKLVPKDEKAGTTQGGKRSDGEQDGTAGS  1000
1001  MDASAQGLLEGIELDGDTLAPMETDEPSSSDSKGKSKITPAMAARIKQIK  1050
1051  PLLSASSRLGRALAELFGLLVKLCVGSPVRQRRSHHAASTTTAPTPAARS  1100
1101  TASALTKLLTKGLSWQPPPYTPTPRFRLTFFICSVGFTSPMLFDERKYPY  1150
1151  HLMLQKFLCSGGHNALFETFNWALSMGGKVPVSEGLEHSDLPDGTGEFLD  1200
1201  AWLMLVEKMVNPTTVLESPHSLPAKLPGGVQSFPQFSALRFLVVTQKAAF  1250
1251  TCIKNLWNRKPLKVYGGRMAESMLAILCHILRGEPVIRERLSKEKEGSRG  1300
1301  EEEAGQEEGGSRREPQVNQQQLQQLMDMGFTREHAMEALLNTSTMEQATE  1350
1351  YLLTHPPPIIGGVVRDLSMSEEDQMMRAIAMSLGQDIPMDQRAESPEEVA  1400
1401  CRKEEEERKAREKQEEEEAKCLEKFQDADPLEQDELHTFTDTMLPGCFHL  1450
1451  LDELPDTVYRVCDLIMTAIKRNGADYRDMILKQVVNQVWEAADVLIKAAL  1500
1501  PLTTSDTKTVSEWISQMATLPQASNLATRILLLTLLFEELKLPCAWVVES  1550
1551  SGILNVLIKLLEVVQPCLQAAKEQKEVQTPKWITPVLLLIDFYEKTAISS  1600
1601  KRRAQMTKYLQSNSNNWRWFDDRSGRWCSYSASNNSTIDSAWKSGETSVR  1650
1651  FTAGRRRYTVQFTTMVQVNEETGNRRPVMLTLLRVPRLSKNSKSSNGQEL  1700
1701  EKTLEESKETDIKHKENKGNDIPLALESTNTEKEASLDETKIGEILIQGL  1750
1751  TEDMVTVLIRACVSMLGVPVDPDTLHATLRLCLRLTRDHKYAMMFAELKS  1800
1801  TRMILNLTQSSGFNGFTPLVTLLLRHIIEDPCTLRHTMEKVVRSAATSGA  1850
1851  GSTTSGVVSGSLGSREINYILRVLGPAACRNPDIFTEVANCCIRIALPAP  1900
1901  RGSGTASDDEFENLRIKGPNAVQLVKTTPLKPSSLPVIPDTIKEVIYDML  1950
1951  NALAAYHAPEEADKSDPKPGGTTQEVGQLLQDMGDDVYQQYRSLTRQSSD  2000
2001  FDTQSGFSLNSQVFAADGAPAETSTTGTSQGEASTPEETREGKKDKEGDR  2050
2051  TSEEGKQKSKGSKPLMPTSTILRLLAELVRSYVGIATLIANYSYTVGQSE  2100
2101  LIKEDCSVLAFVLDHLLPHTQNAEDKDTPALARLFLASLAAAGSGTDAQV  2150
2151  ALVNEVKAALGRALAMAESTEKHARLQAVMCIISTIMESCPSTSSFYSSA  2200
2201  TAKTQHNGMNNIIRLFLKKGLVNDLARVPHSLDLSSPNMANTVNAALKPL  2250
2251  ETLSRIVNQPSSLFGSKSASSKNKSEQDAQGASQDSSSHQQDPGEPGEAE  2300
2301  VQEEDHDVTQTEVADGDIMDGEAETDSVVIAGQPEVLSSQEMQVENELED  2350
2351  LIDELLERDGGSGNSTIIVSRSGEDESQEDVLMDEAPSNLSQASTLQANR  2400
2401  EDSMNILDPEDEEEHTQEEDSSGSNEDEDDSQDEEEEEEEDEEDDQEDDE  2450
2451  GEEGDEDDDDDGSEMELDEDYPDMNASPLVRFERFDREDDLIIEFDNMFS  2500
2501  SATDIPPSPGNIPTTHPLMVRHADHSSLTLGSGSSTTRLTQGIGRSQRTL  2550
2551  RQLTANTGHTIHVHYPGNRQPNPPLILQRLLGPSAAADILQLSSSLPLQS  2600
2601  RGRARLLVGNDDVHIIARSDDELLDDFFHDQSTATSQAGTLSSIPTALTR  2650
2651  WTEECKVLDAESMHDCVSVVKVPIVNHLEFLRDEELEERREKRRKQLAEE  2700
2701  ETKIIDKGKEDKENRDQSAQCTVTKTNDSTEQNVSDGTPMPDSYPTTPSS  2750
2751  TDAPTSESKETLGTLQPSQQQPALPPPPSLGEIPQELQSPAEEVANSTQL  2800
2801  LMPIELEELGPTRPSGEAETTQMELSPAPTITSLSPERAEDSDALTAVSS  2850
2851  QLEGSPMDTSSLASCTLEEAVGDTPAAGSSEQPTAGSSTPGDAPSVVAEV  2900
2901  QGRPDVSRESNQPPEDSSPPASSESSSTRDSAVAISGADSRGILEEPLPS  2950
2951  TSSEEEDPLAGISLPEGVDPSFLAALPDDIRREVLQNQLGIRPPTRSAPS  3000
3001  SNSSAPAVVGNPGVTEVSPEFLAALPPAIQEEVLAQQRAEQQRRELAQNA  3050
3051  SSDTPMDPVTFIQTLPSDLRRSVLEDMEDSVLAVMPPDIAAEAQALRREQ  3100
3101  EARQRQLMHERLFGHSSTSALSAILRSPAFTSRLSGNRGVQYTRLAVQRG  3150
3151  GTFQMGGSSSHNRPSGSNVDTLLRLRGRLLLDHEALSCLLVLLFVDEPKL  3200
3201  NTSRLHRVLRNLCYHAQTRHWVIRSLLSILQRSSESELCIETPKLSTSEE  3250
3251  RGKKSSKSCASSSHENRPLDLLHKMESKSSNQLSWLSVSMDAALGCRTNI  3300
3301  FQIQRSGGRKHTEKHASSGSTVHIHPQAAPVVCRHVLDTLIQLAKVFPSH  3350
3351  FTQQRTKETNCESDRERGSKQACSPCSSQSSSSGICTDFWDLLVKLDNMN  3400
3401  VSRKGKNSVKSVPVSSGGEGETSPHSLEASPLGQLMNMLSHPVIRRSSLL  3450
3451  TEKLLRLLSLISIALPENKVSEVQTNSSNSGSSTAATSNTSTTTTTTTTA  3500
3501  TAPTPTPPAATTPVTSAPALVAATAISTITVAASTTVTTPTTATTTVSTS  3550
3551  TTKGSKSPAKVGEGGSGIDFKMVSSGLTENQLQLSVEVLTSHSCSEEGLE  3600
3601  DAANVLLQLSRGDSGTRDTVLKLLLNGARHLGYTLCKQIGTLLAELREYN  3650
3651  LEQQRRAQCETLSPDGLPEEQPQTTKLKGKMQSRFDMAENVVIVASQKRP  3700
3701  LGGRELQLPSMSMLTSKTSTQKFFLRVLQVIIQLRDDTRRANKKAKQTGR  3750
3751  LGSSGLGSASSIQAAVRQLEAEADAIIQMVREGQRARRQQQAATSESSNQ  3800
3801  SETSVRREESPMDVDQPSPSAQDTQSIVISDGTPQGEKEKEEKPPELPLL  3850
3851  SEQLSLDELWDMLGECLKELEESHDQHAVLVLQPAVEAFFLVHATERESK  3900
3901  PPVRDTRESQLAHIKDEPPPLSPAPLTPATPSSLDPFFSREPSSMHISSS  3950
3951  LPPDTQKFLRFAETHRTVLNQILRQSTTHLADGPFAVLVDYIRVLDFDVK  4000
4001  RKYFRQELERLDEGLRKEDMAVHVRRDHVFEDSYRELHRKSPEEMKNRLY  4050
4051  IVFEGEEGQDAGGLLREWYMIISREMFNPMYALFRTSPGDRVTYTINPSS  4100
4101  HCNPNHLSYFKFVGRIVAKAVYDNRLLECYFTRSFYKHILGKSVRYTDME  4150
4151  SEDYHFYQGLVYLLENDVSTLGYDLTFSTEVQEFGVCEVRDLKPNGANIL  4200
4201  VTEENKKEYVHLVCQMRMTGAIRKQLAAFLEGFYEIIPKRLISIFTEQEL  4250
4251  ELLISGLPTIDIDDLKSNTEYHKYQSNSIQIQWFWRALRSFDQADRAKFL  4300
4301  QFVTGTSKVPLQGFAALEGMNGIQKFQIHRDDRSTDRLPSAHTCFNQLDL  4350
4351  PAYESFEKLRHMLLLAIQECSEGFGLA                         4377

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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