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

NucPred

Fetching Q61554 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MRRGGLLEVALAFALLLESYTSHGADANLEAGSLKETRANRAKRRGGGGH    50
  51  DALKGPNVCGSRYNAYCCPGWKTLPGGNQCIVPICRHSCGDGFCSRPNMC   100
 101  TCPSGQISPSCGSRSIQHCSIRCMNGGSCSDDHCLCQKGYIGTHCGQPVC   150
 151  ESGCLNGGRCVAPNRCACTYGFTGPQCERDYRTGPCFTVVSNQMCQGQLS   200
 201  GIVCTKTLCCATVGRAWGHPCEMCPAQPHPCRRGFIPNIRTGACQDVDEC   250
 251  QAIPGMCQGGNCINTVGSFECKCPAGHKFNEVSQKCEDIDECSTIPGVCD   300
 301  GGECTNTVSSYFCKCPPGFYTSPDGTRCVDVRPGYCYTALANGRCSNQLP   350
 351  QSITKMQCCCDLGRCWSPGVTVAPEMCPIRSTEDFNKLCSVPLVIPGRPE   400
 401  YPPPPIGPLPPVQPVPPGYPPGPVIPAPRPPPEYPYPSPSREPPRVLPFN   450
 451  VTDYCQLVRYLCQNGRCIPTPGSYRCECNKGFQLDIRGECIDVDECEKNP   500
 501  CTGGECINNQGSYTCHCRAGYQSTLTRTECRDIDECLQNGRICNNGRCIN   550
 551  TDGSFHCVCNAGFHVTRDGKNCEDMDECSIRNMCLNGMCINEDGSFKCIC   600
 601  KPGFQLASDGRYCKDINECETPGICMNGRCVNTDGSYRCECFPGLAVGLD   650
 651  GRVCVDTHMRSTCYGGYRRGQCVKPLFGAVTKSECCCASTEYAFGEPCQP   700
 701  CPAQNSAEYQALCSSGPGMTSAGTDINECALDPDICPNGICENLRGTYKC   750
 751  ICNSGYEVDITGKNCVDINECVLNSLLCDNGQCRNTPGSFVCTCPKGFVY   800
 801  KPDLKTCEDIDECESSPCINGVCKNSPGSFICECSPESTLDPTKTICIET   850
 851  IKGTCWQTVIDGRCEININGATLKSECCSSLGAAWGSPCTICQLDPICGK   900
 901  GFSRIKGTQCEDINECEVFPGVCKNGLCVNSRGSFKCECPNGMTLDATGR   950
 951  ICLDIRLETCFLKYDDEECTLPIAGRHRMDACCCSVGAAWGTEECEECPL  1000
1001  RNSREYEELCPRGPGFATKDITNGKPFFKDINECKMIPSLCTHGKCRNTI  1050
1051  GSFKCRCDSGFALDSEERNCTDIDECRISPDLCGRGQCVNTPGDFECKCD  1100
1101  EGYESGFMMMKNCMDIDECQRDPLLCRGGICHNTEGSYRCECPPGHQLSP  1150
1151  NISACIDINECELSANLCPHGRCVNLIGKYQCACNPGYHPTHDRLFCVDI  1200
1201  DECSIMNGGCETFCTNSDGSYECSCQPGFALMPDQRSCTDIDECEDNPNI  1250
1251  CDGGQCTNIPGEYRCLCYDGFMASEDMKTCVDVNECDLNPNICLSGTCEN  1300
1301  TKGSFICHCDMGYSGKKGKTGCTDINECEIGAHNCGRHAVCTNTAGSFKC  1350
1351  SCSPGWIGDGIKCTDLDECSNGTHMCSQHADCKNTMGSYRCLCKDGYTGD  1400
1401  GFTCTDLDECSENLNLCGNGQCLNAPGGYRCECDMGFVPSADGKACEDID  1450
1451  ECSLPNICVFGTCHNLPGLFRCECEIGYELDRSGGNCTDVNECLDPTTCI  1500
1501  SGNCVNTPGSYTCDCPPDFELNPTRVGCVDTRSGNCYLDIRPRGDNGDTA  1550
1551  CSNEIGVGVSKASCCCSLGKAWGTPCELCPSVNTSEYKILCPGGEGFRPN  1600
1601  PITVILEDIDECQELPGLCQGGKCINTFGSFQCRCPTGYYLNEDTRVCDD  1650
1651  VNECETPGICGPGTCYNTVGNYTCICPPDYMQVNGGNNCMDMRRSLCYRN  1700
1701  YYADNQTCDGELLFNMTKKMCCCSYNIGRAWNKPCEQCPIPSTDEFATLC  1750
1751  GSQRPGFVIDIYTGLPVDIDECREIPGVCENGVCINMVGSFRCECPVGFF  1800
1801  YNDKLLVCEDIDECQNGPVCQRNAECINTAGSYRCDCKPGYRLTSTGQCN  1850
1851  DRNECQEIPNICSHGQCIDTVGSFYCLCHTGFKTNVDQTMCLDINECERD  1900
1901  ACGNGTCRNTIGSFNCRCNHGFILSHNNDCIDVDECATGNGNLCRNGQCV  1950
1951  NTVGSFQCRCNEGYEVAPDGRTCVDINECVLDPGKCAPGTCQNLDGSYRC  2000
2001  ICPPGYSLQNDKCEDIDECVEEPEICALGTCSNTEGSFKCLCPEGFSLSS  2050
2051  TGRRCQDLRMSYCYAKFEGGKCSSPKSRNHSKQECCCALKGEGWGDPCEL  2100
2101  CPTEPDEAFRQICPFGSGIIVGPDDSAVDMDECKEPDVCRHGQCINTDGS  2150
2151  YRCECPFGYILEGNECVDTDECSVGNPCGNGTCKNVIGGFECTCEEGFEP  2200
2201  GPMMTCEDINECAQNPLLCAFRCVNTYGSYECKCPVGYVLREDRRMCKDE  2250
2251  DECAEGKHDCTEKQMECKNLIGTYMCICGPGYQRRPDGEGCIDENECQTK  2300
2301  PGICENGRCLNTLGSYTCECNDGFTASPTQDECLDNREGYCFSEVLQNMC  2350
2351  QIGSSNRNPVTKSECCCDGGRGWGPHCEICPFEGTVAYKKLCPHGRGFMT  2400
2401  NGADIDECKVIHDVCRNGECVNDRGSYHCICKTGYTPDITGTACVDLNEC  2450
2451  NQAPKPCNFICKNTEGSYQCSCPKGYILQEDGRSCKDLDECATKQHNCQF  2500
2501  LCVNTIGGFTCKCPPGFTQHHTACIDNNECTSDINLCGSKGVCQNTPGSF  2550
2551  TCECQRGFSLDQSGASCEDVDECEGNHRCQHGCQNIIGGYRCSCPQGYLQ  2600
2601  HYQWNQCVDENECLSAHVCGGASCHNTLGSYKCMCPTGFQYEQFSGGCQD  2650
2651  INECGSSQAPCSYGCSNTEGGYLCGCPPGYFRIGQGHCVSGMGMGRGGPE  2700
2701  PPASSEMDDNSLSPEACYECKINGYPKRGRKRRSTNETDASDIQDGSEME  2750
2751  ANVSLASWDVEKPASFAFNISHVNNKVRILELLPALTTLMNHNRYLIESG  2800
2801  NEDGFFKINQKEGVSYLHFTKKKPVAGTYSLQISSTPLYKKKELNQLEDR  2850
2851  YDKDYLSGELGDNLKMKIQILLH                             2873

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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