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

NucPred

Fetching P98092 from www.uniprot.org...

The NucPred score for your sequence is 0.44 (see score help below)

   1  MRGGRDPVPVPVLGDYAMVCAKNGIILQWRYNVKECELSCTGGQQYTVCA    50
  51  DSCLRKCSDTALAASGQCKPVCVEGCACSPSQLLDDNGVCVPVAKCPCIH   100
 101  KGLQFNAGYKEIRPGRRERELCTCVGARWDCKPATPEEIQNYPPAEDLRS   150
 151  NSTAQNMEFTTCETSEPLTCKNMHLPPSTQTAECRPGCQCKKGQVLDTAS   200
 201  KRCVPATQCPCHHAGRSYPDGHLMQEECNKCECKNGNWSCTQRKCAGVCG   250
 251  AWGDSHVNTFDGTQYDFEGVCTYLLAKGAMDGTDGFDVEIQNVPCGTTGA   300
 301  TCSKSVTLKVGGAGNEEIVSLTKNAPIPDISKLKRIKMRKAGAYVFLDVP   350
 351  SLGMSLQWDRGLRVYVKIDTMWQGRVKGLCGNYNGDMRDDFQTPSGGGMS   400
 401  ESSALIFADSWKLKPTCPKPQPVIDHCKQRPERKEWAQSVCGALKRYPFS   450
 451  LCAGEVGAGAYVARCERDACDAGADCECACAALAAYAHACAHRGVTFNWR   500
 501  TNDLCPMQCDEVCSNYDSCVSACPVETCDNILYYAETTARCEQDTCVEGC   550
 551  KPKKSCPEGSVYKNDSTTECVPRAKCKPVCMTLDGGREVLEGEIIEEDAC   600
 601  HTCRCSKKHKVCTGQPCSTEAPRIQATSSSAEPATERPHEPLKCVTGWTP   650
 651  WINRGPAEIGPDGQSVESEPLPKPNELQIGKPMCKPEMMKKIECRTVNDH   700
 701  KTPKETGLNVECSLENGLVCEEPEKTCPDFEIKVYCECEEPQDTSPPVTV   750
 751  TSEASSEPVSTTLATTTSRCPPGEVYQACAYKCDRLCDHFKKTLIAKGRC   800
 801  ISEMCVDGCVDESVASNGCEGSSRWRDERTCVPVKDCTCYNDGQIVKPGG   850
 851  VTESGCIKCQCLDNSLYCDSKDCVSLNIPHQGSTHLPYIVRPVSTTITST   900
 901  TTTTTTSTTTTTTTPEPTETTTETTVPLIIKSTVSPPPECSPDNYIDLVM   950
 951  GDEPLPDTAFSASSEFSEIFAPHNARLNRGPTNSGAGSWNPKVNNDKQYI  1000
1001  QVELPRREPIYGVVLQGSPIFDQYVTSYEIMYGDDGNTFSTVDGPDGKPK  1050
1051  IFRGPIDNTHPVKQMISPPIEAKVVRIRPLTWHDEISLRLEIIGCAEPLT  1100
1101  TETSEPSPTSESPLQCTEPLGLIGELPLENIQVSSNSEEKDYLSINGNRG  1150
1151  WKPLYNTPGWVMFDFTGPRNITGILTKGGNDGWVTSYKVLYTSDFETFNP  1200
1201  VIDKDGKEKIFPANFDGIVSVTNEFHPPIRARYLKVLPQKWNKNIELRIE  1250
1251  PIGCFEPYPEILRSLPEEEEGREEPQVVRKEYGMSQEREMPNCHICPGVE  1300
1301  AKECTCSYPEYFDGENCVPRAECPCVESFMTYPVGSTFRGANCDECVCKL  1350
1351  GGTTECKPFKECQCDDESLVPKLSPTTCDCTCEPCTNGTKICKTSKLCLA  1400
1401  LESWCDGVQDCPDDERDCTTSTARTTTTEPTVVTTVAPTQAATAPPTTTT  1450
1451  PKPVVECPKVECPPGYIISYTTGSSSSYSRAFSSDLPPPRPRYSYQRYYR  1500
1501  GRSTGGYSGYAKTGYSKGGFSKGGFSKGGYGYPSIPRSNQAFTLDKPALT  1550
1551  NKQPTSKEECAQFKCISKLPAFKPGVVPPPVACSVVTCPAGYTLKLDKVP  1600
1601  TGYNKCPQYECVPPLERPVFCNMTGRTFNTFDGMEYKYDVCFHMLARDNK  1650
1651  FDAWLIIVRKNCRLDGCTNELIVMQDDQLIQVKPNMMVTYNNYEYTIEQT  1700
1701  KKICFQKNSFDVDRLGNGISITSRKYNFTVLFNKEGDVKIGVLKKHMGGV  1750
1751  DGLCGAYDGSLANERRLPDGRVATSIDEFGRSWAKPGVPADACAPRVASA  1800
1801  HKQRRAWDLCNVIAEEPFSQCGKVLNLDKWRHICLEKICECTDLVVNGTK  1850
1851  RTEEQCRCLVLQQMAAECLAADAGVDLASWRLMMDCPADCPPPLVHYDCY  1900
1901  RKRCEETCAPYPNAARACPAQEGQCSPGCYCPDGKLRKGDQCVLPADCLD  1950
1951  CTCTGVGTPAKYTTFEGDDLPFLGNCTYLASRDRNQTGEHKYQVYATNGP  2000
2001  CDDNANIVCTKIVHLIYEKNVIHISKDPTTKKLRTVIGKTAVFKYPVKEN  2050
2051  WGTISLLNGQDVSVTLPDIHVELTVSQLNLEFAVRVPTFLYGNRTEGLCG  2100
2101  VCAGYQDFLVTSNGTVTDDFDLYGKSWQASPEKLTELEVPSDEQCDAPPP  2150
2151  PAPCTPPPPDNNTCYHLYNADRFGACHALVEPQPYVESCEADECGGHGPC  2200
2201  DALQRYAAACAELGLCLPDWRRELCPYPCEEPFVYRACVDCERTCDNYEQ  2250
2251  LQTSPEKCTNKPVEGCFCPEGKVRVNNTCIEPGKCFPCGVDGHYAGDEWQ  2300
2301  EDASTLCACARSPHGTALVGCRATSCAPPVCAHGEDLRTAPPPPGQCCPE  2350
2351  YDCVAKPEAQCKETKKIVCDYGQVLKQKTNPSGCKEYFCECKPSSECEVI  2400
2401  PPESEVEIVEAGIHREIDNSGCCPRVSLVCRPETCPKPPHCPQFQTLASV  2450
2451  NITGKCCPEYKCELPKDKCIVTLEWEAAAKGGEKPREKPQTVLKDLEAVW  2500
2501  LDGPCRSCECALSGAGPAATCAVSACPAVVSSELFVLEPRPVPFACCPEP  2550
2551  VQVACRHQDNVYKVGEKWKSPTDVCETYECAADGDGKLQRLAAVQRCDRH  2600
2601  CQPGWKYVPAEADSGQCCGKCEPVACVVDGEEKPIGEKWTSSDFCTNFTC  2650
2651  VNLNGTLQVQSSNETCPEISDAERKQFVLKEQKVPGKCCPKIEREACTSG  2700
2701  RSDIPGRRELDVDRELVRELPMRAGRGRRPALRGLRAALRDRLPTRLEVL  2750
2751  PAPAECCGRCKPSPASWKGGRGPSGRARERPVGESWTSADFCTNYTCADL  2800
2801  HGTLQVQSSNETCPEVSEAVKKQFVLKEEKIPGKCCPKVEPVACRDGDKI  2850
2851  YQEVQVWTTPDPCTNRTCRREDGQLSVGRTVEHCERQCRRGWTYSPPAAD  2900
2901  HCCGRCVQSACLVDDQLKEPGSTWSSADNCTTFSCDRSGEEVFVTSATEH  2950
2951  CPDVSACDPADIVNTTCCQICNEKPQALSKCVLRASELRHCRSDPHPMGA  3000
3001  HGLCVNKFPITGFTEVHGSCDSGTIYNNQTGTHESACECCQAAKYSGVSV  3050
3051  RLTCEDGTVRPHRVATPARCHCAACGPGLTKHPKPGHASYTGTKNPVQPE  3100
3101  RDREYVIPDISSASGEARRNHDSNYITTLIISF                   3133

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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