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

NucPred

Fetching O13368 from www.uniprot.org...

The NucPred score for your sequence is 0.28 (see score help below)

   1  MIQQFTLLFLYLSFATAKAITGIFNSIDSLTWSNAGNYAFKGPGYPTWNA    50
  51  VLGWSLDGTSANPGDTFILNMPCVFKFTASQKSVDLTADGVKYATCQFYS   100
 101  GEEFTTFSSLKCTVNNNLRSSIKALGTVTLPIAFNVGGTGSSVDLEDSKC   150
 151  FTAGTNTVTFNDGSKKLSIAVNFEKSTVDQSGYLTTSRFMPSLNKIATLY   200
 201  VAPQCENGYTSGTMGFSTSYGDVAIDCSNVHIGISKGVNDWNHPVTSESF   250
 251  SYTKSCSSFGISITYQNVPAGYRPFIDAYISPSDNNQYQLSYKNDYTCVD   300
 301  DYWQHAPFTLKWTGYKNSDAGSNGIVIVATTRTVTDSTTAVTTLPFNPSV   350
 351  DKTKTIEILQPIPTTTITTSYVGVTTSYSTKTAPIGETATVIVDVPYHTT   400
 401  TTVTSEWTGTITTTTTRTNPTDSIDTVVVQVPSPNPTTTTTQFWSESFTS   450
 451  TTTITNSLKGTDSVIVREPHNPTVTTTEFWSESFATTETITSKPEGTDSV   500
 501  IVREPHNPTVTTTEFWSESYATTETITNGPEGTDSVIVREPHNPTVTTTK   550
 551  FWSESYATTETITNKPEGTDSVIVKEPYNPTVTTTEFWSESYATTETITN   600
 601  GPEGTDSVIVREPHNPTVTTTEFWSESYATTETITTGPLGTDSIVIHDPL   650
 651  EESSSTTAIESSDSNISSSAQESSSSVEQSSSIVGLSSSSDIPLSSDMPS   700
 701  SSSTGLTSSESSTVSSYDSDSSSSIESSTLSSSDRCSSSISDTTSFWDSS   750
 751  SSDLESTSITWSSSIDAQSSHLVQSVSNSISTSQELSSSSSEESSTFATD   800
 801  ALVSSDASSILSSDTSSYYPSSTISSSDDFPHTIAGESDSLSISFITSTV   850
 851  EISSDSVSLTSDPASSFDSSSSLNSDSSSSPSSDQSDILTSSSFSTLVVP   900
 901  SFSLSSSSSLSLTYPHYVNSTTYHASESESSSVASPSMASESANDDTYTL   950
 951  SESTDTTSSIGTDSSTVTFCRRDNGDGCIVTGMPSSSIDSEQTSDVTTTS  1000
1001  SFVASSTPTSAEQSITDNPNIDSSQTSASSSTKSSVSVSDTVVNSILLSE  1050
1051  TSTLSSDDSTSSDTSISSTTNSDTGNINAGSSHTSTASIKESSIQKTGVT  1100
1101  LSSSYLSTKLSSTSDITIELITTELITTELTTIEDNEPNTFTSTPSSHSE  1150
1151  IFSSDNSVLSKQVDRESTIKTSPTTDVTTVSSLSVHSTEASTATLGENSF  1200
1201  SNVASTPSNIATSLRSTSSSSNHATESSGTVKSEASAEAIPSPPTSTDNR  1250
1251  LSYSTEEAKGITYANSGSTNNLITESQVAAPTDSTSVLIENPVVTSTFDD  1300
1301  NSSAAVDQPSKTKSIEESIMNPDSTNETNNGFIATLSQAQVPSSSIHSEL  1350
1351  ISTTTAKTTDASMNGDSAASNSQPTTLIQQVATSSYNQPLITTYAGSSSA  1400
1401  TKHPSWLLKFISVALFFFL                                 1419

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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