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

NucPred

Fetching Q9BYK8 from www.uniprot.org...

The NucPred score for your sequence is 0.70 (see score help below)

   1  MAPPGSTLLPNSPAATRGPSLARLCALVDLCLGCSRCTQRLNESTYVLRR    50
  51  VEHDCSREILLARFKQATKSKVWRVVGCRPTFPRPLCYQVCHYYSPGLGC   100
 101  RRHRNRCTFARSREEALVWTFERQHNLQRLWLKAEVQGSGAQGGAGRAAD   150
 151  AILTEFGGRFELLCSLCFRRCPPCICRVDPQGQCPEHGACPSLLAHVSAE   200
 201  GRRKQQFVVVRPRPRAGQPPAYCRFVGRGQPCWRGESRCQFAHSAVEMAV   250
 251  WEAEQLGGLQRGDLLTPPAPDGDGRTAPLGQPPGAQLYCPACLVTCHSQE   300
 301  AFENHCASSEHAQMVAFDQALPWEHRSPPPGLSKFELCPKPDLCEYGDAC   350
 351  TKAHSAQELQEWVRRTQAVELRGQAAWQDGLVPYQERLLAEYQRSSSEVL   400
 401  VLAETLDGVRVTCNQPLMYQAQERKTQYSWTFAVHSEEPLLHVALLKQEP   450
 451  GADFSLVAPGLPPGRLYARGERFRVPSSTADFQVGVRVQAASFGTFEQWV   500
 501  VFDFGRRPVLLQKLGLQLGQGRRPGPCRNLALGHPEEMERWHTGNRHVVP   550
 551  GVERTAEQTALMAKYKGPALALEFNRSSVASGPISPTNYRQRMHQFLYEE   600
 601  EAAQQQLVAKLTLRGQVFLKTALQTPALNMLFAPPGALYAEVPVPSSLMP   650
 651  DTDQGFLLGRAVSTALVAPVPAPDNTVFEVRLERRASSEQALWLLLPARC   700
 701  CLALGLQPEARLVLEVQFQIDPMTFRLWHQAVDTLPEEQLVVPDLPTCAL   750
 751  PRPWSVPPLRRGNRKQELAVALIAGWGPGDGRRVPPLLIYGPFGTGKTYT   800
 801  LAMASLEVIRRPETKVLICTHTNSAADIYIREYFHSHVSGGHPEATPLRV   850
 851  MYTDRPLSQTDPVTLQYCCLTDDRQAFRPPTRAELARHRVVVTTTSQARE   900
 901  LRVPVGFFSHILIDEAAQMLECEALTPLAYASHGTRLVLAGDHMQVTPRL   950
 951  FSVARARAAEHTLLHRLFLCYQQETHEVARQSRLVFHENYRCTDAIVSFI  1000
1001  SRHFYVAKGNPIHARGKVPPHPRHYPLMFCHVAGSPDRDMSMASWLNLAE  1050
1051  IAQVVEKVQEAYNTWPSCWGGREQRCICVVSHGAQVSALRQELRRRDLGQ  1100
1101  VSVGSFEILPGRQFRVVVLSTVHTCQSLLSPGALAPEFFTDARVLNTVLT  1150
1151  RAQSQLVVVGDAVALCSFGACGKLWESFIRECVERHSVCPEGLSMEQVEQ  1200
1201  GVAQRRRWPPRGTQAGAAGNWEAAPEPVGDLAEEQAAVVTAMVKAEPGDE  1250
1251  ALSPASRDITATTAQTEAAAAPAGDAVKEDVVPGACAAGAAAAAGVESTE  1300
1301  AEDAEADFWPWDGELNADDAILRELLDESQKVMVTVGEDGLLDTVARPES  1350
1351  LQQARLYENLPPAALRKLLHAEPERYRHCSFVPETFERASAIPLDDASSG  1400
1401  PIQVRGRLDCGMAFAGDEVLVQLLSGDKAPEGRLRGRVLGVLKRKRHELA  1450
1451  FVCRMDTWDPRIMVPINGSVTKIFVAELKDPSQVPIYSLRKGRLQRVGLE  1500
1501  RLTAEARHSRLFWVQIVLWRQGFYYPLGIVREVLPEASTWEQGLRILGLE  1550
1551  YSLRVPPSDQATITKVLQKYHTELGRVAGRREDCRAFLTFTVDPQGACNL  1600
1601  DDALSVRDLGPRCEVAVHITDVASFVPRDGVLDVEARRQGAAFYAPGREP  1650
1651  VPMLPASLCQDVLSLLPGRDRLAISLFLTMEKASGQLKSLRFAPSVVQSD  1700
1701  RQLSYEEAEEVIRQHPGAGRELPARLDSVDACVVAACYFSRLLRRHRLRS  1750
1751  DCFYEQPDEDGTLGFRAAHIMVKEYMIQFNRLVAEFLVGSECTRTVTPLR  1800
1801  WQPAPRSQQLKALCEKHGDRVPLSLHLGHHLHGGGGSPPDTRLHLLASLW  1850
1851  KQVQFAARTQDYEQMVDLVTTDDMHPFLAPAGRDLRKALERSAFGRCARG  1900
1901  HQQQGGHYSLQVDWYTWATSPIRRYLDVVLQRQILLALGHGGSAYSARDI  1950
1951  DGLCQAFSLQHALAQSYQRRARSLHLAVQLKAQPLDKLGFVVDVEAGSRC  2000
2001  FRLLFPSNRETLPDPCPVPYGSLQLAEHPHALAGRPGLRLLWRRRVYSAQ  2050
2051  GSSPPLPLPGTVPDPHTLAVETALWKQLLELVELQRWPEAAALIQEKGEA  2100
2101  SQRRELVQVQRSHCGHFLEVARELGSGDTLQVQLGTSLQHGFLVPSPQLW  2150
2151  TVAPGFSLCLEHVERPGDCFSGRVYRAPRDRYRDVDEYACVWEPFCALES  2200
2201  ATGAVAENDSVTLQHLSVSWEASRTPQGQLQGAFRLEAAFLEENCADINF  2250
2251  SCCYLCIRLEGLPAPTASPRPGPSSLGPGLNVDPGTYTWVAHGQTQDWDQ  2300
2301  ERRADRQEAPRRVHLFVHHMGMEKVPEEVLRPGTLFTVELLPKQLPDLRK  2350
2351  EEAVRGLEEASPLVTSIALGRPVPQPLCRVIPSRFLERQTYNIPGGRHKL  2400
2401  NPSQNVAVREALEKPFTVIQGPPGTGKTIVGLHIVFWFHKSNQEQVQPGG  2450
2451  PPRGEKRLGGPCILYCGPSNKSVDVLAGLLLRRMELKPLRVYSEQAEASE  2500
2501  FPVPRVGSRKLLRKSPREGRPNQSLRSITLHHRIRQAPNPYSSEIKAFDT  2550
2551  RLQRGELFSREDLVWYKKVLWEARKFELDRHEVILCTCSCAASASLKILD  2600
2601  VRQILVDEAGMATEPETLIPLVQFPQAEKVVLLGDHKQLRPVVKNERLQN  2650
2651  LGLDRSLFERYHEDAHMLDTQYRMHEGICAFPSVAFYKSKLKTWQGLRRP  2700
2701  PSVLGHAGKESCPVIFGHVQGHERSLLVSTDEGNENSKANLEEVAEVVRI  2750
2751  TKQLTLGRTVEPQDIAVLTPYNAQASEISKALRREGIAGVAVSSITKSQG  2800
2801  SEWRYVLVSTVRTCAKSDLDQRPTKSWLKKFLGFVVDPNQVNVAVTRAQE  2850
2851  GLCLIGDHLLLRCCPLWRSLLDFCEAQQTLVPAGQVRVCRRPTMPS      2896

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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