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

NucPred

Fetching Q9NRL2 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MPLLHRKPFVRQKPPADLRPDEEVFYCKVTNEIFRHYDDFFERTILCNSL    50
51 VWSCAVTGRPGLTYQEALESEKKARQNLQSFPEPLIIPVLYLTSLTHRSR 100
101 LHEICDDIFAYVKDRYFVEETVEVIRNNGARLQCRILEVLPPSHQNGFAN 150
151 GHVNSVDGETIIISDSDDSETQSCSFQNGKKKDAIDPLLFKYKVQPTKKE 200
201 LHESAIVKATQISRRKHLFSRDKLKLFLKQHCEPQDGVIKIKASSLSTYK 250
251 IAEQDFSYFFPDDPPTFIFSPANRRRGRPPKRIHISQEDNVANKQTLASY 300
301 RSKATKERDKLLKQEEMKSLAFEKAKLKREKADALEAKKKEKEDKEKKRE 350
351 ELKKIVEEERLKKKEEKERLKVEREKEREKLREEKRKYVEYLKQWSKPRE 400
401 DMECDDLKELPEPTPVKTRLPPEIFGDALMVLEFLNAFGELFDLQDEFPD 450
451 GVTLEVLEEALVGNDSEGPLCELLFFFLTAIFQAIAEEEEEVAKEQLTDA 500
501 DTKDLTEALDEDADPTKSALSAVASLAAAWPQLHQGCSLKSLDLDSCTLS 550
551 EILRLHILASGADVTSANAKYRYQKRGGFDATDDACMELRLSNPSLVKKL 600
601 SSTSVYDLTPGEKMKILHALCGKLLTLVSTRDFIEDYVDILRQAKQEFRE 650
651 LKAEQHRKEREEAAARIRKRKEEKLKEQEQKMKEKQEKLKEDEQRNSTAD 700
701 ISIGEEEREDFDTSIESKDTEQKELDQDMVTEDEDDPGSHKRGRRGKRGQ 750
751 NGFKEFTRQEQINCVTREPLTADEEEALKQEHQRKEKELLEKIQSAIACT 800
801 NIFPLGRDRMYRRYWIFPSIPGLFIEEDYSGLTEDMLLPRPSSFQNNVQS 850
851 QDPQVSTKTGEPLMSESTSNIDQGPRDHSVQLPKPVHKPNRWCFYSSCEQ 900
901 LDQLIEALNSRGHRESALKETLLQEKSRICAQLARFSEEKFHFSDKPQPD 950
951 SKPTYSRGRSSNAYDPSQMCAEKQLELRLRDFLLDIEDRIYQGTLGAIKV 1000
1001 TDRHIWRSALESGRYELLSEENKENGIIKTVNEDVEEMEIDEQTKVIVKD 1050
1051 RLLGIKTETPSTVSTNASTPQSVSSVVHYLAMALFQIEQGIERRFLKAPL 1100
1101 DASDSGRSYKTVLDRWRESLLSSASLSQVFLHLSTLDRSVIWSKSILNAR 1150
1151 CKICRKKGDAENMVLCDGCDRGHHTYCVRPKLKTVPEGDWFCPECRPKQR 1200
1201 SRRLSSRQRPSLESDEDVEDSMGGEDDEVDGDEEEGQSEEEEYEVEQDED 1250
1251 DSQEEEEVSLPKRGRPQVRLPVKTRGKLSSSFSSRGQQQEPGRYPSRSQQ 1300
1301 STPKTTVSSKTGRSLRKINSAPPTETKSLRIASRSTRHSHGPLQADVFVE 1350
1351 LLSPRRKRRGRKSANNTPENSPNFPNFRVIATKSSEQSRSVNIASKLSLQ 1400
1401 ESESKRRCRKRQSPEPSPVTLGRRSSGRQGGVHELSAFEQLVVELVRHDD 1450
1451 SWPFLKLVSKIQVPDYYDIIKKPIALNIIREKVNKCEYKLASEFIDDIEL 1500
1501 MFSNCFEYNPRNTSEAKAGTRLQAFFHIQAQKLGLHVTPSNVDQVSTPPA 1550
1551 AKKSRI 1556

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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