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

NucPred

Fetching Q86X10 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MYSEWRSLHLVIQNDQGHTSVLHSYPESVGREVANAVVRPLGQVLGTPSV    50
51 AGSENLLKTDKEVKWTMEVICYGLTLPLDGETVKYCVDVYTDWIMALVLP 100
101 KDSIPLPVIKEPNQYVQTILKHLQNLFVPRQEQGSSQIRLCLQVLRAIQK 150
151 LARESSLMARETWEVLLLFLLQINDILLAPPTVQGGIAENLAEKLIGVLF 200
201 EVWLLACTRCFPTPPYWKTAKEMVANWRHHPAVVEQWSKVICALTSRLLR 250
251 FTYGPSFPAFKVPDEDASLIPPEMDNECVAQTWFRFLHMLSNPVDLSNPA 300
301 IISSTPKFQEQFLNVSGMPQELNQYPCLKHLPQIFFRAMRGISCLVDAFL 350
351 GISRPRSDSAPPTPVNRLSMPQSAAVSTTPPHNRRHRAVTVNKATMKTST 400
401 VSTAHASKVQHQTSSTSPLSSPNQTSSEPRPLPAPRRPKVNSILNLFGSW 450
451 LFDAAFVHCKLHNGINRDSSMTAITTQASMEFRRKGSQMSTDTMVSNPMF 500
501 DASEFPDNYEAGRAEACGTLCRIFCSKKTGEEILPAYLSRFYMLLIQGLQ 550
551 INDYVCHPVLASVILNSPPLFCCDLKGIDVVVPYFISALETILPDRELSK 600
601 FKSYVNPTELRRSSINILLSLLPLPHHFGTVKSEVVLEGKFSNDDSSSYD 650
651 KPITFLSLKLRLVNILIGALQTETDPNNTQMILGAMLNIVQDSALLEAIG 700
701 CQMEMGGGENNLKSHSRTNSGISSASGGSTEPTTPDSERPAQALLRDYAL 750
751 NTDSAAGLLIRSIHLVTQRLNSQWRQDMSISLAALELLSGLAKVKVMVDS 800
801 GDRKRAISSVCTYIVYQCSRPAPLHSRDLHSMIVAAFQCLCVWLTEHPDM 850
851 LDEKDCLKEVLEIVELGISGSKSKNNEQEVKYKGDKEPNPASMRVKDAAE 900
901 ATLTCIMQLLGAFPSPSGPASPCSLVNETTLIKYSRLPTINKHSFRYFVL 950
951 DNSVILAMLEQPLGNEQNDFFPSVTVLVRGMSGRLAWAQQLCLLPRGAKA 1000
1001 NQKLFVPEPRPVPKNDVGFKYSVKHRPFPEEVDKIPFVKADLSIPDLHEI 1050
1051 VTEELEERHEKLRSGMAQQIAYEIHLEQQSEEELQKRSFPDPVTDCKPPP 1100
1101 PAQEFQTARLFLSHFGFLSLEALKEPANSRLPPHLIALDSTIPGFFDDIG 1150
1151 YLDLLPCRPFDTVFIFYMKPGQKTNQEILKNVESSRTVQPHFLEFLLSLG 1200
1201 WSVDVGRHPGWTGHVSTSWSINCCDDGEGSQQEVISSEDIGASIFNGQKK 1250
1251 VLYYADALTEIAFVVPSPVESLTDSLESNISDQDSDSNMDLMPGILKQPS 1300
1301 LTLELFPNHTDNLNSSQRLSPSSRMRKLPQGRPVPPLGPETRVSVVWVER 1350
1351 YDDIENFPLSELMTEISTGVETTANSSTSLRSTTLEKEVPVIFIHPLNTG 1400
1401 LFRIKIQGATGKFNMVIPLVDGMIVSRRALGFLVRQTVINICRRKRLESD 1450
1451 SYSPPHVRRKQKITDIVNKYRNKQLEPEFYTSLFQEVGLKNCSS 1494

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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