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

NucPred

Fetching P35555 from www.uniprot.org...

The NucPred score for your sequence is 0.71 (see score help below)

   1  MRRGRLLEIALGFTVLLASYTSHGADANLEAGNVKETRASRAKRRGGGGH    50
  51  DALKGPNVCGSRYNAYCCPGWKTLPGGNQCIVPICRHSCGDGFCSRPNMC   100
 101  TCPSGQIAPSCGSRSIQHCNIRCMNGGSCSDDHCLCQKGYIGTHCGQPVC   150
 151  ESGCLNGGRCVAPNRCACTYGFTGPQCERDYRTGPCFTVISNQMCQGQLS   200
 201  GIVCTKTLCCATVGRAWGHPCEMCPAQPHPCRRGFIPNIRTGACQDVDEC   250
 251  QAIPGLCQGGNCINTVGSFECKCPAGHKLNEVSQKCEDIDECSTIPGICE   300
 301  GGECTNTVSSYFCKCPPGFYTSPDGTRCIDVRPGYCYTALTNGRCSNQLP   350
 351  QSITKMQCCCDAGRCWSPGVTVAPEMCPIRATEDFNKLCSVPMVIPGRPE   400
 401  YPPPPLGPIPPVLPVPPGFPPGPQIPVPRPPVEYLYPSREPPRVLPVNVT   450
 451  DYCQLVRYLCQNGRCIPTPGSYRCECNKGFQLDLRGECIDVDECEKNPCA   500
 501  GGECINNQGSYTCQCRAGYQSTLTRTECRDIDECLQNGRICNNGRCINTD   550
 551  GSFHCVCNAGFHVTRDGKNCEDMDECSIRNMCLNGMCINEDGSFKCICKP   600
 601  GFQLASDGRYCKDINECETPGICMNGRCVNTDGSYRCECFPGLAVGLDGR   650
 651  VCVDTHMRSTCYGGYKRGQCIKPLFGAVTKSECCCASTEYAFGEPCQPCP   700
 701  AQNSAEYQALCSSGPGMTSAGSDINECALDPDICPNGICENLRGTYKCIC   750
 751  NSGYEVDSTGKNCVDINECVLNSLLCDNGQCRNTPGSFVCTCPKGFIYKP   800
 801  DLKTCEDIDECESSPCINGVCKNSPGSFICECSSESTLDPTKTICIETIK   850
 851  GTCWQTVIDGRCEININGATLKSQCCSSLGAAWGSPCTLCQVDPICGKGY   900
 901  SRIKGTQCEDIDECEVFPGVCKNGLCVNTRGSFKCQCPSGMTLDATGRIC   950
 951  LDIRLETCFLRYEDEECTLPIAGRHRMDACCCSVGAAWGTEECEECPMRN  1000
1001  TPEYEELCPRGPGFATKEITNGKPFFKDINECKMIPSLCTHGKCRNTIGS  1050
1051  FKCRCDSGFALDSEERNCTDIDECRISPDLCGRGQCVNTPGDFECKCDEG  1100
1101  YESGFMMMKNCMDIDECQRDPLLCRGGVCHNTEGSYRCECPPGHQLSPNI  1150
1151  SACIDINECELSAHLCPNGRCVNLIGKYQCACNPGYHSTPDRLFCVDIDE  1200
1201  CSIMNGGCETFCTNSEGSYECSCQPGFALMPDQRSCTDIDECEDNPNICD  1250
1251  GGQCTNIPGEYRCLCYDGFMASEDMKTCVDVNECDLNPNICLSGTCENTK  1300
1301  GSFICHCDMGYSGKKGKTGCTDINECEIGAHNCGKHAVCTNTAGSFKCSC  1350
1351  SPGWIGDGIKCTDLDECSNGTHMCSQHADCKNTMGSYRCLCKEGYTGDGF  1400
1401  TCTDLDECSENLNLCGNGQCLNAPGGYRCECDMGFVPSADGKACEDIDEC  1450
1451  SLPNICVFGTCHNLPGLFRCECEIGYELDRSGGNCTDVNECLDPTTCISG  1500
1501  NCVNTPGSYICDCPPDFELNPTRVGCVDTRSGNCYLDIRPRGDNGDTACS  1550
1551  NEIGVGVSKASCCCSLGKAWGTPCEMCPAVNTSEYKILCPGGEGFRPNPI  1600
1601  TVILEDIDECQELPGLCQGGKCINTFGSFQCRCPTGYYLNEDTRVCDDVN  1650
1651  ECETPGICGPGTCYNTVGNYTCICPPDYMQVNGGNNCMDMRRSLCYRNYY  1700
1701  ADNQTCDGELLFNMTKKMCCCSYNIGRAWNKPCEQCPIPSTDEFATLCGS  1750
1751  QRPGFVIDIYTGLPVDIDECREIPGVCENGVCINMVGSFRCECPVGFFYN  1800
1801  DKLLVCEDIDECQNGPVCQRNAECINTAGSYRCDCKPGYRFTSTGQCNDR  1850
1851  NECQEIPNICSHGQCIDTVGSFYCLCHTGFKTNDDQTMCLDINECERDAC  1900
1901  GNGTCRNTIGSFNCRCNHGFILSHNNDCIDVDECASGNGNLCRNGQCINT  1950
1951  VGSFQCQCNEGYEVAPDGRTCVDINECLLEPRKCAPGTCQNLDGSYRCIC  2000
2001  PPGYSLQNEKCEDIDECVEEPEICALGTCSNTEGSFKCLCPEGFSLSSSG  2050
2051  RRCQDLRMSYCYAKFEGGKCSSPKSRNHSKQECCCALKGEGWGDPCELCP  2100
2101  TEPDEAFRQICPYGSGIIVGPDDSAVDMDECKEPDVCKHGQCINTDGSYR  2150
2151  CECPFGYILAGNECVDTDECSVGNPCGNGTCKNVIGGFECTCEEGFEPGP  2200
2201  MMTCEDINECAQNPLLCAFRCVNTYGSYECKCPVGYVLREDRRMCKDEDE  2250
2251  CEEGKHDCTEKQMECKNLIGTYMCICGPGYQRRPDGEGCVDENECQTKPG  2300
2301  ICENGRCLNTRGSYTCECNDGFTASPNQDECLDNREGYCFTEVLQNMCQI  2350
2351  GSSNRNPVTKSECCCDGGRGWGPHCEICPFQGTVAFKKLCPHGRGFMTNG  2400
2401  ADIDECKVIHDVCRNGECVNDRGSYHCICKTGYTPDITGTSCVDLNECNQ  2450
2451  APKPCNFICKNTEGSYQCSCPKGYILQEDGRSCKDLDECATKQHNCQFLC  2500
2501  VNTIGGFTCKCPPGFTQHHTSCIDNNECTSDINLCGSKGICQNTPGSFTC  2550
2551  ECQRGFSLDQTGSSCEDVDECEGNHRCQHGCQNIIGGYRCSCPQGYLQHY  2600
2601  QWNQCVDENECLSAHICGGASCHNTLGSYKCMCPAGFQYEQFSGGCQDIN  2650
2651  ECGSAQAPCSYGCSNTEGGYLCGCPPGYFRIGQGHCVSGMGMGRGNPEPP  2700
2701  VSGEMDDNSLSPEACYECKINGYPKRGRKRRSTNETDASNIEDQSETEAN  2750
2751  VSLASWDVEKTAIFAFNISHVSNKVRILELLPALTTLTNHNRYLIESGNE  2800
2801  DGFFKINQKEGISYLHFTKKKPVAGTYSLQISSTPLYKKKELNQLEDKYD  2850
2851  KDYLSGELGDNLKMKIQVLLH                               2871

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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