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

NucPred

Fetching P98133 from www.uniprot.org...

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

   1  MRRGGLLEVALGFTVLLASYTSHGADTNLEAGNVKETRANRAKRRGGGGH    50
  51  DALKGPNVCGSRYNAYCCPGWKTLPGGNQCIVPICRHSCGDGFCSRPNMC   100
 101  TCPSGQIAPSCGSRSIQHCNIRCMNGGSCSDDHCLCQKGYIGTHCGQPVC   150
 151  ESGCLNGGRCVAPNRCACTYGFTGPQCERDYRTGPCFTVISNQMCQGQLS   200
 201  GIVCTKTLCCATVGRAWGHPCEMCPAQPHPCRRGFIPNIRTGACQDVDEC   250
 251  QAIPGLCQGGNCINTVGSFECKCPAGHKFNEVSQKCEDIDECSTIPGICD   300
 301  GGECTNTVSSYFCKCPPGFYTSPDGTRCIDVRPGYCYTALANGRCSNQLP   350
 351  QSITKMQCCCDVGRCWSPGVTVAPEMCPIRATEDFNKLCSVPMVIPERPG   400
 401  YPPPPLGPVPPVQPVPPGFPPGPQIMIPRPPVEYPYPSREPPRVLPVNVT   450
 451  DYCQLFRYLCQNGRCIPTPGSYRCECNKGFQLDLRGECIDVDECEKNPCA   500
 501  GGECINTQGSYTCQCRPGYQSTLTRTECRDIDECLQNGRICNNGRCINTD   550
 551  GSFHCVCNAGFHVTRDGKNCEDMDECSIRNMCLNGMCINEDGSFKCICKP   600
 601  GFQLASDGRYCKDINECETPGICMNGRCVNTDGSYRCECFPGLAVGLDGR   650
 651  VCVDTHMRSTCYGGYKRGQCVKPLFGAVTKSECCCASTEYAFGEPCQPCP   700
 701  SQNSAEYQALCSSGPGITSAGSDINECALDPDICPNGICENLRGTYKCIC   750
 751  NSGYEVDSTGKNCVDINECVLNSLLCDNGQCRNTPGSFVCTCPKGFIYKP   800
 801  ELKTCEDIDECESSPCINGVCKNSPGSFICECSSESTLDPTKTICIETIK   850
 851  GTCWQTVIDGRCEININGATLKSQCCSSLGAAWGSPCTPCQVDPICGKGY   900
 901  SRIKGTQCEDIDECEVFPGVCKNGLCVNSKGSFKCQCPSGMTLDATGRIC   950
 951  LDIRLETCFLRYEDEECTLPVAGRHRMDACCCSVGAAWGTEECEECPVRN  1000
1001  TPEYEELCPRGPGFATKEITNGKRFFKDINECKMIPNLCTHGKCRNTIGS  1050
1051  FKCRCDSGFALDSEERNCTDIDECRISPDLCGRGQCVNTPGDFECKCDEG  1100
1101  YESGFMMMKNCMDIDECQRDPLLCRGGVCLNTEGSYRCECPPGHQLAPNI  1150
1151  SACIDINECELSAHLCPHGRCVNLIGKYQCACNPGYHSTPDRLFCVDIDE  1200
1201  CSIMNGGCETFCTNSEGSYECSCQPGFALMPDQRSCTDIDECEDNPNICD  1250
1251  GGQCTNIPGEYRCLCYDGFMASEDMKTCVDVNECDLNPNICLSGTCENTK  1300
1301  GSFICHCDMGYSGKKGKTGCTDINECEIGAHNCDRHAVCTNTAGSFKCSC  1350
1351  SPGWIGDGIKCTDLDECSNGTHMCSQHADCKNTMGSYRCLCKEGYTGDGF  1400
1401  TCTDLDECSENLNLCGNGQCLNAPGGYRCECDMGFVPSADGKACEDIDEC  1450
1451  SLPNICVFGTCHNLPGLFRCECEIGYELDRSGGNCTDVNECLDPTTCISG  1500
1501  NCVNTPGSYTCDCPPDFELNPTRVGCVDTRSGNCYLDIRPRGDNGDTACS  1550
1551  NEIGVGVSKASCCCSLGKAWGTPCELCPPVNTSEYKILCPGGEGFRPNPI  1600
1601  TVILEDIDECQELPGLCQGGKCINTFGSFQCRCPTGYYLNEDTRVCDDVN  1650
1651  ECETPGICGPGTCYNTVGNYTCICPPDYMQVNGGNNCMDMRRSLCYRNYY  1700
1701  ADNQTCDGELLFNMTKKMCCCSYNIGRAWNKPCEQCPIPSTDEFATLCGS  1750
1751  QRPGFVIDIYTGLPVDIDECREIPGVCENGVCINMVGSFRCECPVGFFYN  1800
1801  DKLLVCEDIDECQNGPVCQRNAECINTAGSYRCDCKPGYRFTSTGQCNDR  1850
1851  NECQEIPNICSHGQCIDTVGSFYCLCHTGFKTNADQTMCLDINECERDAC  1900
1901  GNGTCRNTIGSFNCRCNHGFILSHNNDCIDVDECATGNGNLCRNGQCINT  1950
1951  VGSFQCQCNEGYEVAPDGRTCVDINECLLDPRKCAPGTCQNLDGSYRCIC  2000
2001  PPGYSLQNDKCEDIDECVEEPEICALGTCSNTEGSFKCLCPDGFSLSSTG  2050
2051  RRCQDLRMSYCYAKFEGGKCSSPKSRNHSKQECCCALKGEGWGDPCELCP  2100
2101  TEPDEAFRQICPYGSGIIVGPDDSAVDMDECKEPDVCKHGQCINTDGSYR  2150
2151  CECPFGYILQGNECVDTDECSVGNPCGNGTCKNVIGGFECTCEEGFEPGP  2200
2201  MMTCEDINECAQNPLLCAFRCVNTYGSYECKCPAGYVLREDRRMCKDEDE  2250
2251  CEEGKHDCAEKQMECKNLIGTYLCICGPGYQRRPDGEGCVDENECQTKPG  2300
2301  ICENGRCLNTRGSYTCECNDGFTASPNQDECLDNREGYCFTEVLQNMCQI  2350
2351  GSSNRNPVTKSECCCDGGRGWGPHCEICPFQGTVAFKKLCPHGRGFMTNG  2400
2401  ADIDECKVIHDVCRNGECVNDRGSYHCICKTGYTPDITGTACVDLNECNQ  2450
2451  APKPCNFICKNTEGSYQCSCPKGYILQEDGRSCKDLDECATKQHNCQFLC  2500
2501  VNTIGSFTCKCPPGFTQHHTACIDNNECTSDINLCGSKGICQNTPGSFTC  2550
2551  ECQRGFSLDPSGASCEDVDECEGNHRCQHGCQNIIGGYRCSCPQGYLQHY  2600
2601  QWNQCVDENECLSAHICGGASCHNTLGSYKCMCPAGFQYEQFSGGCQDIN  2650
2651  ECGSAQAPCSYGCSNTEGGYLCACPPGYFRIGQGHCVSGMGMGRGNPEPP  2700
2701  ASGEMDDNSLSPEACYECKINGYPKRGRKRRSANETDASNIEDQPEIEAN  2750
2751  VSLASWDVEKTAVFAFNISHISNKVRILELLPALTTLTNHNRYLIESGNE  2800
2801  NGFFKINQKEGISYLHFTKKKPVAGTYSLQISSTPLYKKKELNQLEDKYD  2850
2851  KDYLSGELGDNLKMKIQILLH                               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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