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

NucPred

Fetching Q86BY9 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MNSQVMYHNVPTPPGNVSLAAAAPDGGLLYAGIRCINYISAPPANGEQPQ    50
  51  VVTMSTRINILALDVSPMWGLGNGGPTKPFAIVGDDLSVQVWDCALGEAV   100
 101  IGHKAHQHQHEARDVRVVHHTTNSVLMSYLANGNILSMDASDLVIYCVAS   150
 151  NTYCRRSTFISPRNHQLTMVRCSPYNDNLFAVGTAMGNVLVCDLRKMNIV   200
 201  YKFHGHKAPICGLAWREVPAAEDEKTNNLALSAEEWRSRNGGQEEKPKTK   250
 251  PPPLTKSKAAESDDPFDIYNFDHLEYEFGAPIAERRRKSSEDCGGEFVGL   300
 301  EKPAGAAVLDFVEACESVKAELLASRQEDKTQHVEVTLHDCEPTKPTGPL   350
 351  SDASTISNKNDASDSTEGSLEVIQYSSSSDDAVIVDGEAAKPKREVLHHI   400
 401  YHQAEVHASGTPQTKSEPQSNLQVVPAISAETISLTSVNSTHLETLLVSI   450
 451  DGDEVMMIWNTNTGAHAGKNYSKSKTAGKLNNVYWLNNHVIVSLSRHQLF   500
 501  FWSVEFERKMLRYKISKDKSHSCHLQDIVSFACDSSKEMIWLCRNNRQIG   550
 551  MMNPKTGRMADFYGTVAFGVRAMAECPDDMNKIALGCSDRRVAFFDISKL   600
 601  TTSCLPIDSVYVSSNVYCLAWSPNCLELAFGTFDGTVGILDVERMKVKTH   650
 651  LRTPHKKEVYSLVWQDHFIYFIVNRVLGFFDLRKSKIEPTIVNCISRPSY   700
 701  LSIRDSFLFVGTDDGLLQIHERDSGMEKSWSPFIRQSALFARYVTDIAWC   750
 751  PLDSNKFAVSGNDRSVYVMEFQPTERNWKTLHTFTANTEKASITSMRWSH   800
 801  TQKHLLLTFHIEGKVCLWNCNAPEKPPLTITYHCPMWCGMFLPTNENIIM   850
 851  CSGKALSVELIDIKDALEGDEKSICPKVDALLNVKWASKSLTQPYAPVLT   900
 901  AAEKKRQRRDQRKAAAKLEVDVANKDQKKIQESVTAVIDNPTNDKCTQET   950
 951  PVEEMLEALSLDKEQNNRSAKECPKCKEQSPDSFTHSRTCLYLTQKELNK  1000
1001  SALEKLAIVLTEDSAKIDKSVLISKLFSSKVMAKELIATELTNLKHSNTK  1050
1051  DIAPLCLAMSTFKLREELEQHIANKTLTERHVSLAPSVSFTLWQDCCRAY  1100
1101  AKQMEEKGYIMHAATYLFSQGMQSEAIKLFLANEYYKEALVHARICLPAT  1150
1151  DPLIKTVINNWLEHLEGTGNFAAAALICVLDNEMLRGYSYLRKYRNCTPE  1200
1201  IADLMDQIKRIGQLGGVLDGCAPNEPIHNGSTAEH                 1235

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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